Patent Publication Number: US-11657617-B1

Title: Presentation of a user interface for confirming unreliable group data

Description:
PRIORITY 
     This application is a continuation of, and claims priority to, U.S. patent application Ser. No. 16/599,819, filed on Oct. 11, 2019, entitled “Generation of Image Gallery For Acquisition of Group Data”, which is hereby incorporated by reference in its entirety. 
     Application Ser. No. 16/599,819 is a continuation of, and claims priority to, U.S. patent application Ser. No. 15/193,552, filed on Jun. 27, 2016, entitled “User Interface For Acquisition Of Group Data”, which is hereby incorporated by reference in its entirety. 
    
    
     BACKGROUND 
     Facilities such as stores, libraries, hospitals, offices, and so forth, may maintain areas in which inventory is stored. Users may enter these areas to replenish items, obtain items, and so forth. It may be desirable to monitor the movement of users within the facility. 
    
    
     
       BRIEF DESCRIPTION OF FIGURES 
       The detailed description is set forth with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The use of the same reference numbers in different figures indicates similar or identical items or features. The figures are not necessarily drawn to scale, and in some figures, the proportions or other aspects may be exaggerated to facilitate comprehension of particular aspects. 
         FIG.  1    illustrates a system to determine information about user entry to a facility and provide interfaces to gather data about that entry, according to some implementations. 
         FIG.  1 A  illustrates a system to determine information about users entering the facility without an associate, according to some implementations. 
         FIG.  1 B  illustrates a system to determine information about which users are members of a group, according to some implementations. 
         FIG.  2    illustrates an overhead view of an entry area which includes various sensors and an associate to facilitate acquisition of data about users entering the facility, according to some implementations. 
         FIG.  2 A  depicts three possible configurations of an entry area, according to some implementations. 
         FIG.  3    depicts an illustration of a user interface to assist in identification of a user entering the facility, according to some implementations. 
         FIG.  4    depicts an illustration of a user interface to acquire input used to determine group data about users entering the facility, according to some implementations. 
         FIG.  5    depicts an illustration of a user interface to acquire input used to determine group data about users entering the facility, according to some implementations. 
         FIG.  6    depicts an illustration of a user interface to acquire input used to determine group data about users entering the facility that also presents information about an identified user, according to some implementations. 
         FIG.  7    depicts an illustration of a user interface to acquire input used to determine group data about users entering the facility by drawing on an image of users, according to some implementations. 
         FIG.  8    depicts an illustration of a user interface to acquire input used to determine group data about users entering the facility that also includes an image of the associate, according to some implementations. 
         FIG.  9    depicts an illustration of a user interface to acquire input used to determine who has exited the facility, according to some implementations. 
         FIG.  10    is a block diagram illustrating a materials handling facility (facility) using the system to gather data about user entry, according to some implementations. 
         FIG.  11    is a block diagram illustrating additional details of the facility and sensors, according to some implementations. 
         FIG.  12    is a block diagram of a server to support operation of the facility, according to some implementations. 
         FIG.  13    depicts a flow diagram of a process for generating group data using input from an associate, according to some implementations. 
         FIG.  14    depicts a flow diagram of a process for identifying a user of the facility, according to some implementations. 
         FIG.  15    depicts a flow diagram of another process for identifying a user of the facility, according to some implementations. 
         FIG.  16    depicts a flow diagram of a process for using an associate to restore tracking in an automated system after a loss, according to some implementations. 
         FIG.  17    depicts a flow diagram of a process for using an associate to identify a user that is unidentified by an automated system, according to some implementations. 
     
    
    
     While implementations are described herein by way of example, those skilled in the art will recognize that the implementations are not limited to the examples or figures described. It should be understood that the figures and detailed description thereto are not intended to limit implementations to the particular form disclosed but, on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope as defined by the appended claims. The headings used herein are for organizational purposes only and are not meant to be used to limit the scope of the description or the claims. As used throughout this application, the word “may” is used in a permissive sense (i.e., meaning having the potential to), rather than the mandatory sense (i.e., meaning must). Similarly, the words “include,” “including,” and “includes” mean “including, but not limited to”. 
     DETAILED DESCRIPTION 
     Described in this disclosure are systems and techniques for determining information about users entering, using, and exiting a facility. The facility may include a materials handling facility that stores items for rent, lease, purchase, checkout, and so forth. The facility may include, or have access to, a facility management system. The facility management system may be configured to maintain information about items, users, condition of the facility, and so forth. For example, the facility management system may maintain data indicative of a number of items at a particular inventory location, a location of the user within the facility, who the user is, what group of users a particular user is a member of, how many items have been picked or placed at the inventory location by the user, requests for assistance, environmental status of the facility, and so forth. 
     Operation of the facility may be facilitated by using one or more sensors to acquire information about occurrences in the facility. The facility management system may process the sensor data from the one or more sensors to determine information such as tracking data, identification data, interaction data, and so forth. The tracking data comprises information indicative of a particular location of a user within the facility at particular times. The identification data provides information that associates the user with a particular identifier, such as a billing account number, user login, and so forth. The interaction data is indicative of action such as picking or placing an item at a particular inventory location, presence of the user at the inventory location, and so forth. For example, the facility management system may use the sensor data to generate interaction data that indicates a type of item a user picked from a particular inventory location, quantity of the pick, and so forth. 
     An inventory location may include shelves, hooks, and so forth, that hold or otherwise support a type of item. Items may be added to (placed) or removed (picked) from the inventory location. Each inventory location may hold a different type of item and may include one or more sensors. The sensors may include weight sensors, capacitive sensors, image sensors, and so forth. Users may move from one inventory location to another within the facility to examine items, pick items, place items, and so forth. The facility management system may use the data from these sensors to determine the interaction data. 
     As users enter and exit the facility, they pass through a designated area that is designed to facilitate identification and tracking of the user. For example, an entry area may include one or more gates through which users may pass to enter the facility. Likewise, users may exit the facility by passing through a gate. In some implementations, the entry area may include gates designated for ingress and gates designated for egress. In other implementations, a separate exit area may be designated. 
     A user of the facility may approach the entry area with a user device. For example, the user device may comprise a smartphone, tablet computer, wearable computing device, and so forth. The user device presents entry credential data that is acquired by the sensor at the gate. For example, the user&#39;s smartphone may present an image of a two-dimensional barcode that is read by a camera at the gate. The entry credential data may be used to associate the user with a particular identifier, such as a billing account number, user login, and so forth. 
     One or more sensors such as image sensors or cameras may be used to track the user as they move within the entry area and also within at least a portion of the facility. Computer vision tracking algorithms may be used to track the user as they travel through various aisles of the facility. Tracking may be discontinued or omitted from particular areas, such as conference rooms or restrooms. 
     Sometimes a group of users may enter the facility. For example, a party of three users may enter. Actions attributed to a member of the group may be aggregated. For example, a pick or place by a user of the group may result in a charge accruing to the billing account associated with the group. Computers may implement algorithms to determine whether a user entering the facility is alone or a member of a group, and if a member of a group who the other members of the group are as well. 
     In some situations, automated systems may experience one or more of a loss of tracking, loss of identification, or low confidence in group membership of the users. Upon determination by an automated system that the output of a situation has been deemed to be unreliable, such as when having a confidence value that is below a threshold value, the judgment of a human operator such as an associate may be utilized. In one implementation, the associate may be on-site at the facility, such as stationed at the entry area. In another implementation, the associate may be off-site, such as at a centralized processing facility or working from home. In yet another implementation, a combination of associates that are on-site and off-site may be utilized. 
     The facility management system may access the sensor data to generate image gallery data. The image gallery data may comprise information associated with a particular user of the facility. The image gallery data may be based on sensor data obtained at a particular time, location, and so forth. For example, the image gallery data may comprise images of the user at about the same time as when they present the user device to the scanner at the gate. The image gallery data may include one or more different views of the user that have been obtained from cameras positioned at different points within the entry area. For example, the image gallery data may include an overhead view, an oblique view, and so forth. Because of the presentation of the entry credential data, the user may be identified at least as being associated with a particular identifier such as a particular billing account. 
     Image gallery data may also be generated at other locations within the facility and at other times. For example, image gallery data may include images obtained of the user while within the facility. In some implementations, the image gallery data may include images acquired both at the entry area and within the facility. The image gallery data may also include other image data, such as an image of the user obtained during a registration process. For example, while setting up an account for the user to access the facility, one or more images of the user may be obtained and stored. The image gallery data may comprise still images, video clips, live video stream, and so forth. In some implementations, other data may be incorporated in or presented with the image gallery data. For example, non-image data such as a count of users passing through the gate at a particular time as generated by sensors at the gate may be presented with the image gallery data. 
     Upon a determination that output is unreliable, sensor data obtained within the facility may be accessed. For example, the identification of a particular user as determined by an automated system may drop below a threshold confidence value at a first time. First image data leading up to the first time and image gallery data associated with currently unidentified users in the facility may be accessed and sent to an associate device. The associate device may present a user interface that displays the first image data and the image gallery data. An associate may use one or more interface elements to select the image presented in the image gallery data that corresponds to the user depicted in the first image data that is unidentified. Associate input data indicative of the selection may be generated and provided to the facility management system. Based on this information, the facility management system may assign the identification indicated by the associate to the now identified user. 
     The physical arrangement of the entry area, such as the placement of the gates may be designed to facilitate a clear distinction between groups of users who may enter the facility. For example, walls, barriers, and so forth, may be used to provide an area before or after passage through the gate at which a group of users may congregate before entering the facility together. 
     In some situations, an automated system may be unable to determine if two or more users are members of a common group or not. For example, during peak usage hours the distance between users may decrease due to crowding. In situations where the determination of a group by the automated system has been deemed unreliable the associate may be utilized. For example, after determining that the determination of the group has dropped below a threshold confidence value, the user interface on an associate device may present image data acquired at the entry area. The associate may observe the image data to make a determination as to who is a member of a particular group. In implementations where the associate is physically present at the entry area, the associate may approach the users and seek clarifying information to make a determination as to group membership. For example, as the associate approaches a first user to engage in conversation, the failure of a second user to remain with the first user may provide information indicative of the second user not belonging to the same group as the first user. The associate may use the associate device to provide associate input data that is then processed by the facility management system to generate group data. 
     The interaction between the automated system and human associates may be asynchronous. The automated system may experience a low confidence event at a first time that is indicative of output from the automated system being deemed unreliable. As a result of the low confidence event, subsequent events may also be low confidence events. Upon receiving the associate input data at a second time, corrections to determinations may be subsequently made and retroactively applied. For example, at the first time, the user may be tracked but not properly identified. While unidentified, the user may pick and place various items. As a result of the lack of identification associated with that user, the confidence value in the determination of who picked and placed those items may be zero. Once identification data has been obtained, such as through the associate input data provided by an associate, the identification may be retroactively applied to the now identified user. As a result, a billing account associated with the now identified user may be debited or credited according to the value of the items picked or placed. By supporting asynchronous operation, the overall accuracy of the output provided by the facility management system is highly accurate while minimizing negative user experience that could result from delays associated in processing the sensor data by an automated system or by utilizing the associate. 
     By using the techniques described herein, operation of the facility may be improved. By using automated systems in conjunction with human associates, users may be able to quickly and with little or no interference enter and exit the facility. Once in the facility, the user may be accurately tracked, identified, and associated with a group (if any). User interactions may be associated with a particular identifier, such as a billing account. Details about interactions between users and items in the facility may be quickly and accurately determined. For example, as items are picked, placed, and so forth, information such as inventory levels based on changes in the count of items at the inventory locations may be readily and more accurately determined. As a result, the facility management system is able to quickly track what item a user has interacted with, maintain up-to-date inventory information, and so forth. 
     Illustrative System 
       FIG.  1    illustrates a system  100  to determine information about user entry to a facility and provide interfaces to gather data about that entry, according to some implementations. 
     A user  102  may be admitted to a facility by passing through a lane  104  in an entry area. The lane  104  may be defined by a gate  106 . In some implementations, the gate  106  may include a movable barrier to control movement of the user  102 . For example, the gate  106  may include computer-controlled panels that may be closed to impede passage of the user  102  or opened to permit passage of the user  102 . 
     The facility may include one or more sensors  108 . For example, the gate  106  may include a barcode sensor  108 ( 1 ) that is built into a pedestal. The barcode sensor  108 ( 1 ) may comprise an image sensor such as a camera, photodetector, or other sensing apparatus designed to read a one or two-dimensional barcode. For example, the barcode sensor may comprise a spinning mirror or microelectromechanical mirror array, configured to sweep with a photodetector to determine changes in intensity of the barcode presented on the display of the user device. As the user  102  approaches the lane  104  they access their user device  110 . The user device  110  or a portion thereof, such as the display, is presented to the barcode sensor  108 ( 1 ). As discussed below, after presentation of the user device  110 , the gate  106  may open and allow the user  102 ( 1 ) entry into the facility. The interior may include one or more image sensors  108 ( 2 ). For example, image sensors  108 ( 2 ) such as cameras may be configured to obtain multiple views of the lane  104  and the user  102 ( 1 ) who is in the lane  104 , and other users  102  in the entry area. 
     An associate  112  may be positioned in the entry area. The associate  112  may be an employee, contractor, or other worker who is tasked with assisting users  102  and aiding their entry into the facility. The associate  112  may have an associate device  114 . The associate device  114  may comprise a computing device that is stationary, portable, wearable, and so forth. For example, the associate device  114  depicted here may comprise a tablet computer. In another example, the associate device  114  may comprise a wearable computing device, such as a head-mounted computing device or a device that uses a head-mounted display. The associate device  114  may present a user interface  116 . The user interface  116  may be used to present information obtained from or based at least in part on one or more sensors  108  of the facility. The user interface  116  may also be used to acquire information such as described below. In some implementations, the associate  112  and the associate device  114  may be physically located elsewhere. For example, the associate  112  and the associate device  114  may be working in another facility. 
     The facility may include a facility management system  118 . The facility management system  118  may access sensor data, user input, and so forth. The facility management system  118  may be configured to perform various functions such maintaining information about entry and exit of users  102  to the facility, tracking users  102  within the facility, determining whether a particular user  102  is associated with a group, tracking changes to a quantity on hand of the items resulting from picking or placing by the user  102 , and so forth. 
     The facility management system  118  may include or have access to an interface module  120 . The interface module  120  may be configured to interact with other devices such as the user device  110 , the gate  106 , the associate device  114 , and so forth. 
     In one implementation, the facility management system  118  may provide entry credential data  122  to the user device  110 . The entry credential data  122  comprises information that may be expressed as an image of a barcode, data encoded within a barcode, token data, and so forth. In some implementations, such as described below, the entry credential data  122  may be provided to the user device  110  responsive to a request. The entry credential data  122  may be valid for use only within a predetermined period of time, for a single use, at a particular location, and so forth. For example, the entry credential data  122  as provided by the facility management system  118  may only be valid to permit a user  102  entry into the facility for five minutes after issuance, or for a particular date and time window. The facility management system  118  may maintain or access information that associates a particular entry credential data  122  with a particular identifier, such as a billing account number, user name, and so forth. 
     During operation, the user device  110  obtains or generates the entry credential data  122  and presents the entry credential data  122  to the sensor  108  at the gate  106 . For example, the entry credential data  122  may be presented as a two-dimensional barcode on a display of the user device  110 . The display of the user device  110  depicting this two-dimensional barcode may be presented to the barcode sensor  108 ( 1 ) which reads the barcode and generates lane data  124 . The lane data  124  may comprise information that was received by the barcode sensor  108 ( 1 ) and may also include information obtained from other sensors  108  associated with the gate  106 . For example, the gate  106  may comprise a plurality of infrared light emitters and infrared light detectors to detect passage of an object, such as legs of the user  102 . In some implementations, the lane data  124  may include or be based at least in part on information from these other sensors  108  at the gate  106 . 
     The facility management system  118  may include an analysis module  126 . The analysis module  126  may perform one or more functions such as determining the presence of a user  102  within a picture, tracking the user  102  as they move through the facility, identifying the user  102 , determining if the user  102  is a member of a group of other users  102 , and so forth. The analysis module  126  may utilize machine learning algorithms, computer vision algorithms, and so forth. The analysis module  126  may process image data  128  obtained from one or more of the image sensors  108 ( 2 ) in the facility. The image data  128  may include two-dimensional images, depth maps that include distance or three-dimensional information, and so forth. For example, the image data  128  may comprise a red-green-blue image with depth or distance data associated with portions of the image, such as individual pixels or groups of pixels in the image. For example, the computer vision algorithms may be used to determine presence of a user  102  by detecting a human face within image data  128 . The analysis module  126  may perform other functions, such as employing blob tracking to track an object such as a person as they move around within the image, and so forth. For example, blob tracking may track a human identified as a user  102 , associate  112 , or someone who is unidentified. The analysis module  126  may perform tracking on an object such as a user  102 , before the identity of the user  102  has been determined, or if the identity of the user  102  has been deemed unreliable. For example, if a user  102  tailgates another user  102  or jumps the gate  106 , the analysis module  126  may still provide tracking for that user  102  who is unidentified. Tailgating occurs when two or more users  102  pass through the gate  106 , or a designated portion of the facility, at about the same time. Tailgating typically involves a second user  102 ( 2 ) walking closely next to the first user  102 ( 1 ) as the first user  102 ( 1 ) passes through the gate  106 . The analysis module  126  may also process sensor data obtained from other sensors  108 , such as the lane data  124  obtained from the barcode sensor  108 ( 1 ) at the gate  106 . 
     In some situations, the automated processes of the analysis module  126  may determine output is unreliable, such as when the output has a confidence value below a threshold value. For example, when the entry area is crowded and there are many users  102  intermixed with one another, the analysis module  126  may have a low confidence value in a determined identity of a particular user  102  or associate  112  depicted in an image obtained by the image sensors  108 ( 2 ). Upon the occurrence of this low confidence event, the facility management system  118  may obtain assistance from a person such as an associate  112 . 
     Assistance of the associate  112  may be employed in various ways. In one implementation, the facility management system  118  may generate presentation data  130  that is provided to the associate device  114 . The associate device  114  may use the presentation data  130  to cause display of the user interface  116 . In one implementation, the presentation data  130  may comprise a Hypertext Markup Language (HTML) document with one or more associated or embedded images. The associate device  114  may execute a rendering engine that processes the presentation data  130  and causes display on the associate device  114 . 
     Continuing the example above in which the confidence value for identification of the user  102  has dropped below a threshold value, image data  128  may be accessed and used to generate presentation data  130 . For example, the presentation data  130  may include images of the user  102  as they present their user device  110  at the gate  106 . Continuing the example, the presentation data  130  may also include images of the unidentified or poorly identified user  102  within the facility. The associate  112  may view this information and either confirm or change the designation of identity. The associate device  114  generates associate input data  132  responsive to the input by the associate  112 . The associate input data  132  is provided to the facility management system  118 . With this data, the analysis module  126  may update the status of the user  102 , assign the identity designated by the associate  112  with the previously unidentified user  102 , and so forth. 
     In another implementation, the facility management system  118  may have a low confidence value in whether two or more users  102  form a group. As depicted in this illustration, the user interface  116  may be provided with presentation data  130  that includes various images obtained by the image sensors  108 ( 2 ). The user interface  116  may accept input from the associate  112  that specifies which users  102  are deemed to be in the group. The associate input data  132  may be indicative of this input and may be provided to the facility management system  118 . The facility management system  118  processes the associate input data  132  and generates group data  134 . The group data  134  associates particular users  102  with a particular group. For example, the group data  134  may indicate that user  102 ( 4 ) and user  102 ( 5 ) are in a common group. Members of a common group may share a common identifier. For example, each user  102  may be affiliated with a particular user identifier. Each of these user identifiers may then be associated with a single common session identifier. For example, a table may store data that indicates “User  102 ( 4 ), User  102 ( 5 ), Group 12291” where “12291” is the group identifier, thus associating the two users  102  as being members of the same group. 
     Different implementations of the user interface  116  are described in more detail with regard to subsequent figures. 
     Users  102  within a group may be identified as discrete individuals but may not have their personal identities known by the facility management system  118 . For example, a foreman of a work crew may have established credentials, registered with the facility management system  118 , and setup a billing account. The workers operating under the direction of the foreman to assist in picking and placing items may not have such accounts. Upon entry into the facility, the foreman and the workers may be associated with a single group. As a result, the facility management system  118  may associate any resulting costs with the billing account of the foreman. Thus, when a worker picks an item from a shelf, the foreman may be billed for the cost of that item. In some implementations, a single user  102  may be deemed to be a group of one. 
     In some implementations, individual users  102  that are tracked within the facility may be assigned a particular identifier that distinguishes them from other users  102 . For example, the user serial number may be issued to a particular user  102  following the scan of their entry credential data  122  at the gate  106 . This user serial number may then later be associated with a particular account identifier, such as a discrete login for that particular user  102 . Continuing the example, a group may comprise a set of user serial numbers. 
     One or more of the various functions described with regard to the modules of the facility management system  118  may in some implementations be performed by other systems. For example, another system may be configured to provide the entry credential data  122 . 
       FIG.  1 A  illustrates a system  136  to determine information about users entering the facility without an associate  112 , according to some implementations. In some implementations, no associate  112  may be present at the facility, and users  102  may enter and exit without interacting with an associate  112 . As described above, identity of the user  102  may be obtained at least in part from one or more of entry credential data  122 , the image data  128 , or other sensor data. 
       FIG.  1 B  illustrates a system  138  to generate group data  134  indicative of which users  102  are members of a group, according to some implementations. In some implementations, instead of, or in addition to gathering group data  134  from an associate  112 , the users  102  may provide information to generate group data  134 . For example, the user interface  116  may be presented on the user device  110  and used to acquire input from one of the users  102 . The user  102  may provide information that indicates they are part of a group, or may provide information they are not affiliated with another group. For example, the user  102  may enter into the user interface  116  on the user device  110  that they are alone. An alert or notification may be sent to the application providing the user interface  116  on the user device  110  of a particular user  102 . For example, user  102 ( 4 ) may receive a notification on their smartphone about some ambiguity as to who is part of their group in the facility. The user  102 ( 4 ) may access the user interface  116  and provide information used to generate group data  134 . Contemporaneously, other users  102  may also be prompted to provide information by way of the user interface  116 . For example, the user  102 ( 3 ) may also receive a notification on their smartphone. Preliminary group data  134  based on input from several users  102  may be analyzed and used to generate final group data  134 . For example, group data  134  that is consistent with input obtained from two different users  102  may be deemed to be the final group data  134 . 
     In some implementations, the user interface  116  may be presented on computing devices accessible within the facility. For example, touchscreen displays to present the user interface  116  may be arranged on pedestals within an entry area, on gates  106 , mounted to walls, and so forth. Users  102 , associates  112 , or both may then utilize these computing devices to provide input via the user interface  116 . 
       FIG.  2    illustrates an overhead view  200  of an entry area  202  which includes various sensors  108 . The entry area  202  may include a plurality of image sensors  108 ( 2 ). In one implementation, each lane  104  may be within the field of view of at least three cameras. Other sensors  108 , such as the barcode sensors  108 ( 1 ) may also be present. 
     In some implementations, the lanes  104  may be reconfigurable to operate in an entry mode, an exit mode, or an entry and exit mode. As depicted here, gates  106 ( 1 )-( 3 ) are configured as entry lanes  204  while gates  106 ( 4 ) and  106 ( 5 ) are configured as exit lanes  206 . During normal operation of the facility, users  102  may enter by way of the entry lanes  204  and leave by way of the exit lanes  206 . In one implementation, the gate  106  may comprise a gate manufactured by Orion Entrance Control Inc. of Laconia, N.H., USA. For example, gate  106  may comprise an optical barrier swing gate design with transparent moveable members to permit or deny passage and the barcode sensor(s)  108 ( 1 ) may be integrated into the pedestals along with other sensors  108 . For example, instead of or in addition to the barcode sensor  108 ( 1 ), a near field communication (NFC) reader may be incorporated into the gate  106 . For example, the entry credential data  122  may be transmitted using NFC or Bluetooth. 
     In other implementations, the entry lanes  204 , exit lanes  206 , or both may omit the gates  106 , instead using other devices to obtain the entry credential data  122 . For example, pedestals may be positioned in the entry area  202  that include barcode sensors  108 ( 1 ). In some implementations, the entry lanes  204 , exit lanes  206 , or both may be delineated using indicia on the floor, such as particular colored tiles. In other implementations, the entry lanes  204 , exit lanes  206 , or both may be delineated using furnishings or decorative items. In yet other implementations, the entry lanes  204 , exit lanes  206 , or both may not be explicitly delineated, instead providing an area for passage of the users  102 . 
     The entry area  202  may be configured to facilitate operation of the sensors  108 . For example, light baffles such as walls, tinted windows, and so forth, may be arranged such that the image sensors  108 ( 2 ) are not impaired by natural light coming in through windows or doors. 
     As described above, the user  102  approaches a lane  104  and uses the user device  110  to provide entry credential data  122  to a scanner in the lane  104 , such as a barcode sensor  108 ( 1 ) as part of a gate  106 . The gate  106  may have a movable member that may be selectively opened or closed to permit or deny, respectively, physical entry to the facility. In one implementation, the gate  106  may prevent physical entry until the entry credential data  122  has been authorized. For example, the gate  106  may open after receiving data from the facility management system  118  indicative of valid entry credential data  122 . In another example, the gate  106  may open after receiving the entry credential data  122  but without confirming whether that entry credential data  122  is valid. Continuing this example, should the entry credential data  122  later be determined to be invalid, an associate  112  may be dispatched to interact with the invalid user  102 . This interaction may include registering the user  102 , escorting them from the facility, and so forth. In another implementation, the gate  106  may remain closed until directed by an associate  112 . For example, presentation of improper entry credential data  122  may result in the associate  112  being summoned or directed to a particular gate  106 . The associate  112  may then assess the situation and determine if entrance should be permitted. If entrance is permitted, the associate  112  may activate a control to open the gate  106  and allow the user  102  to enter the facility. If entrance is not permitted, the gate  106  may remain closed, and the associate  112  may escort the user  102  from the facility. 
     Entry to the facility may be restricted to users  102  who otherwise possess valid entry credential data  122 . For example, if the number of people within the facility is within a threshold value of a maximum occupancy capacity of the facility, entrance may be denied until some users  102  leave. In another example, users  102  may not be permitted to enter during particular times or when particular operations are taking place, such as during movement of machinery, cleaning, and so forth. 
     Authorization of the entry credential data  122  may be performed in some implementations by the computing device controlling the gate  106 . The gate  106  may be connected to a network and receive pre-authorization data indicative of what entry credential data  122  will be deemed valid. For example, pre-authorization data may include a list of accepted token values, inputs for an algorithm used to determine if the entry credential data  122  is valid, and so forth. The gate  106  receives the entry credential data  122  using the barcode sensor  108 ( 1 ). The gate  106  may then determine that the entry credential data  122  is authorized using the pre-authorization data. Responsive to this determination, the gate  106  may open the movable member to allow the user  102  to enter the facility. The gate  106  may then generate the lane data  124  and send the lane data  124  to the facility management system  118 . 
     In some implementations, the facility management system  118  may process the image data  128  to determine one or more gestures associated with presentation of the user device  110  to the barcode sensor  108 ( 1 ). For example, the computer vision algorithm may be used to process the image data  128  to determine that a portion of the image data  128  that corresponds to an area near the barcode sensor  108 ( 1 ) has changed from a first time to a second time. This change may be the result of a “swipe” or passage of the user device  110  near the barcode sensor  108 ( 1 ). Continuing the example, the change may comprise a sequence of images that depict a change in the pixels of an area corresponding to the barcode sensor  108 ( 1 ) that exceed a threshold value. The computer vision algorithm may utilize object recognition to recognize one or more of the hand of the user  102  or the user device  110 . In other implementations, other techniques may be used to recognize a particular gesture made by the user  102 . A time associated with the gesture of the “swipe” may be determined, such as a timestamp of one or more of the image data  128 . If the time associated with the gesture is within a threshold period of time at which data was obtained by the barcode sensor  108 ( 1 ), the facility management system  118  may use this information to confirm that a user  102  was present at the gate  106  when the entry credential data  122  was presented. In some implementations, the generation of the image gallery data  212  may be based at least in part on the information indicative of the gesture associated with presenting the user device  110  at the gate  106 . For example, the image gallery data  212  may comprise the image data  128  that is within one second of a time of the gesture associated with presenting the user device  110  to the barcode sensor  108 ( 1 ). 
     In a situation where the user  102  is part of a group, the user  102  may pass back their user device  110  to the other members of the group for them to use to scan and enter the facility. Alternatively, the user  102  with the user device  110  may pass their user device  110  across the barcode sensor  108 ( 1 ) multiple times to correspond to the number of users  102  in the group. Continuing the example, if there are three users  102  in the group, the user  102  may scan their user device  110  three times. As each of the users  102  in the group pass through the gate  106 , they are associated with the group of the first user  102 ( 1 ). 
     The facility management system  118  may be configured to avoid adding the associate  112  to a group of users  102 . For example, there may be a designated associate area  208  within the entry area  202 . Persons that are standing within this designated associate area  208  may be prevented from being automatically added to the group. In some implementations, the associate  112  may be recognized based on a tracking device, visual indicia, and so forth. For example, the associate  112  may have a name tag or identification card that includes one or more features that are distinguishable within the image data  128 . Continuing the example, the name tag may include a barcode, may have a particular color, and so forth. 
     Grouping of users  102  may also be facilitated by the use of one or more designated grouping areas  210  present within the entry area  202 . For example, either the entry area  202  before or after the gates  106  may be a designated grouping area  210 . The designated grouping area  210  may include a section of flooring. When more than one user  102  stands within the designated grouping area  210 , the analysis module  126  may determine those users  102  to be members of a common group. In another implementation, the user  102  may provide input using the user device  110  to indicate the number of individuals in their group. This information may then be used by the analysis module  126  to determine the group data  134 . 
     During operation of the facility, users  102  pass in and out of the facility at the lanes  104  generally without personal interaction with the associate  112 . However, in the event of a low confidence determination by an automated system, the associate  112  may be called upon to use the user interface  116  of the associate device  114  to provide associate input data  132 . The associate  112  may generate the associate input data  132  based on a review of sensor data presented within the user interface  116 , personal observation, as a result of conversation with the user  102 , and so forth. For example, if a second user  102 ( 2 ) should enter the facility by tailgating behind the first user  102 ( 1 ), the associate  112  may approach the second user  102 ( 2 ) and ask the second user  102 ( 2 ) to re-enter or present entry credential data  122 . 
     As described above, the image data  128  may comprise images obtained from one or more of the image sensors  108 ( 2 ) in the entry area  202 . The image data  128  may comprise still images, video clips, live stream data, and so forth. The facility management system  118  may generate image gallery data  212 . The image gallery data  212  may comprise at least a portion of the sensor data obtained by the sensors  108  within the facility. For example, the image gallery data  212  may include images of the user  102  that have been cropped to depict just that user  102 . The cropping may be performed manually, automatically, or as a combination of manual and automatic operation. For example, the manual cropping may be performed in response to the input of an associate  112 . Continuing the example, the automatic cropping may utilize image processing techniques to recognize a user&#39;s  102  head and crop the image around where the head is. 
     The image gallery data  212  may also present other information such as a name of the user  102 , image data  128  obtained during registration of the user  102 , and so forth. In some implementations, the image gallery data  212  may comprise images obtained in the entry area  202  at the time of entry. For example, the image gallery data  212  may comprise images of the user  102  obtained contemporaneously with their presentation of the user device  110  at the gate  106 . The image gallery data  212  may include images of different users  102 , images of the same user  102  but obtained from different cameras, and so forth. The image gallery data  212  provides a reference point of known information that may be subsequently used by the associate  112  or the facility management system  118 . 
       FIG.  2 A  depicts three possible configurations of an entry area  202 , according to some implementations. A first entry configuration  214  depicts the use of partitions  216  to form lanes  104 . As depicted here, two partitions  216  may be placed in an approximately arcuate layout to form three lanes  104 . As users  102  enter the facility, they are directed to pass through one of the lanes  104 . In some implementations, these partitions  216  may include one or more sensors  108 , while in other implementations, the partitions  216  may omit sensors  108  and comprise inert furniture without electronics. A particular associate  112  may be tasked with handling users  102  entering through a particular lane  104 . For example, a first associate  112 ( 1 ) may be responsible for assisting the entry of users  102  passing through a first lane  104 ( 1 ), while a second associate  112 ( 2 ) is responsible for the users  102  passing through a second lane  104 ( 2 ), and so forth. The associate devices  114  may be handheld, free standing, mounted to an article of furniture, and so forth. 
     A second entry configuration  218  depicts an open floor plan in which no gates  106  or partitions  216  are present within the entry area  202 . Associates  112  are arranged within the entry area  202  to assist users  102  who are entering. In some implementations, the associates  112  may be affiliated with a designated associate area  208 . For example, associate  112 ( 2 ) may be designated to stand within the designated associate area  208 ( 2 ). The associate  112  may not be restricted to remain within the designated associate area  208 ( 2 ). For example, the associate  112  may move around in the entry area  202  as needed to assist users  102 . Once assistance is complete, the associate  112  may return to the designated associate area  208 . 
     A third entry configuration  220  depicts an open floor plan in which no gates  106 , partitions  216 , or associates  112  are present in the entry area  202 . In this implementation, users  102  enter the facility without being constrained to a particular lane  104 . The entry credential data  122  may be obtained wirelessly. For example, the user device  110  may wirelessly transmit the entry credential data  122  to a sensor  108  in the facility. In another example, the image data  128  may be processed using facial recognition techniques to identify the user  102 . In some implementations, data from multiple sensors  108  may be used to determine the identity of the users  102  entering the facility. 
     Illustrative User Interfaces 
       FIG.  3    depicts an illustration  300  of the user interface  116  configured to assist in identification of a user  102  entering the facility, according to some implementations. The user interface  116  depicted here may be presented on the associate device  114 , or on another computing device. The presentation data  130  may be used to cause the display on the associate device  114  of this and the other user interfaces  116  described herein. 
     The user interface  116  may include a presentation section  302  and an image gallery section  304 . The user interface  116  may present information that is associated with a low confidence event, such as an ambiguity as to identification of a user  102  who has entered the facility. 
     The presentation section  302  may include different portions of the image data  128 . For example, a plurality of thumbnails  306  are depicted. Selection by the associate  112  of one of these thumbnails  306  may result in their presentation as a presented image  308 . The presented image  308  may comprise still images, video clip, live stream, and so forth. For example, where the presented image  308  comprises a video clip, the video clip may be configured to play once and then stop, repeat indefinitely until paused, rock back and forth (wherein the video is presented in normal sequence and then presented in reversed sequence with the image appearing to be going backwards), and so forth. The image data  128  presented in the presentation section  302  may be image data  128  that is associated with a particular time, particular location within the facility, and so forth. For example, in this illustration, identification of the user  102  that entered the facility has a low confidence value and is presented to the associate  112  for resolution. The image data  128  presented in the presentation section  302  depicted here comprises image data  128  that was obtained contemporaneously with the scan of the entry credential data  122  in the vicinity of the location within the entry area  202  where the gate  106  is located. 
     One or more image interface elements  310  may be present within the user interface  116 . The image interface elements  310  include, but are not limited to, one or more of a time index control, a pause control, a play control, a rewind control, a fast-forward control, a refresh control, a change camera control, and so forth. For example, the image interface elements  310  may allow the associate  112  to manipulate the video clip, view image data  128  from a different camera, and so forth. The time index control may allow the user  102  to change presentation to different portions of the image data  128 , such as different times within the video clip. In some implementations, the image interface elements  310  may be visible control icons such as depicted here. In other implementations, image interface elements  310  may comprise gestures. For example, a swipe to the left may rewind while a swipe the right may fast forward through the video clip that is presented as the presented image  308 . 
     The image interface elements  310  may present additional information obtained from other sensors  108 . In one implementation, the time index control may be used to present timeline data. For example, vertical lines may be used to indicate when entry credential data  122  was scanned by the barcode sensor  108 ( 1 ) at the gate  106 . Additional information may also be presented. In another example, visual indicia such as color, icons, text, and so forth, may be used to indicate the number of times the same set of entry credential data  122  were received, and so forth. Continuing this example, two vertical lines of the same color, with the same label, and so forth, as presented on the time index control may indicate the scan of the same code occurred twice. 
     Selection of the initial image data  128  to be presented within the presented image  308  may be automatic or manual. For example, the facility management system  118  may attempt to determine a video clip in which the image has the least amount of blurriness. This video clip may then be presented first as the initial presented image  308  of the presentation section  302 . In another example, each lane  104  may be associated with a default camera, and the presented image  308  may be image data  128  obtained by the default camera. In yet another example, a particular associate  112  may specify a preferred camera from which image data  128  is to be initially presented as the presented image  308 . 
     Overlaid onto the presented image  308 , or otherwise incorporated therewith may be other information generated by the facility management system  118 . Designator indicia  312  may be associated with the depiction of a user  102  within the image data  128 . The designator indicia  312  may be indicative of detection of a particular object in the image data  128 . For example, the designator indicia  312  may comprise a bounding box that surrounds an object appearing within the image data  128  that has been determined by a computer vision algorithm or manual input as being a person. In another example, the designator indicia  312  may comprise a change in background color of the image as presented, an icon presented adjacent to the object, an arrow, a visual effect, an outline, and so forth. Continuing the example, the visual effect may comprise blurring, highlighting, changing contrast, changing coloring, and so forth. In one implementation, the area around the object may be blurred leaving the object unblurred. 
     Identifier indicia  314  may also be presented within the presented image  308 . The identifier indicia  314  provides a human-readable designation that differentiates one user  102  from another user  102 . The identifier indicia  314  may comprise text, an icon, graphic, and so forth. The identifier indicia  314  may be independent of an actual identification of the user  102 . For example, as depicted here, the identifier indicia  314  comprise sequential alphabetic characters. In other implementations, the identifier indicia  314  may be associated with actual identification, such as a username, first name, surname, and so forth. 
     Presence of the designator indicia  312  in the user interface  116  may be used as a visual cue to the associate  112  that a user  102  has been recognized as a user  102 . Presence of the identifier indicia  314  in the user interface  116  may be used as a visual cue to the associate  112  that a user  102  has been identified and is being tracked. 
     By using the information overlaid on the presented image  308 , the associate  112  is able to quickly make decisions with regard to particular situations. For example, in this illustration, an untracked user  316  is present. The associate  112  is able to determine that the user  102  is untracked because there is no designator indicia  312  or identifier indicia  314  presented in the user interface  116  with respect to that person. 
     In the situation depicted here in  FIG.  3   , the associate  112  is being asked to help determine who entered the facility after the entry scan. The image gallery section  304  may be used to present at least a portion of the image gallery data  212 . As described above, the image gallery data  212  may include gallery images  320  obtained at a particular time, location, and so forth. In this illustration, the image gallery data  212  presented in the image gallery section  304  includes gallery images  320  of the users  102  obtained at their entry to the facility. In some implementations, the image gallery data  212  may include information obtained from earlier, such as during previous visits to the facility, during a registration process, and so forth. 
     In situations where the facility management system  118  has made a determination, information about that determination may be used to determine placement of one or more elements within the user interface  116 . For example, the associate  112  has been prompted to use the user interface  116  to resolve a low confidence identification. A highest confidence image  318  may be presented more prominently, such as higher up within the user interface  116 , at a size that is larger than other images, with the border or other visual indicia for emphasis, and so forth. In some implementations, the image data  128  having the highest confidence value may be automatically selected. If the low confidence determination is actually correct, the associate  112  may then use an interface element  322  to submit the information. However, if the selection is incorrect or needs further amendment, the associate  112  may activate one or more other interface elements  322  to make the changes that are necessary. The interface elements  322  may comprise graphical elements such as invisible controls, buttons, sliders, combo boxes, list boxes, radio buttons, and so forth. Invisible controls may comprise controls that are associated with another element in the user interface  116 , such as the designator indicia  312 , the identifier indicia  314 , and so forth. For example, the designator indicia  312  may be displayed, providing output to the person using the user interface  116 . In another example, the designator indicia  312  may be associated with an invisible control that is manifested within the boundary of the designator indicia  312 . In the situation where a touchscreen is used, by touching within the border of the designator indicia  312 , the person may activate or deactivate the selection of the particular user  102  associated with the designator indicia  312  as being a member of a group. 
     Continuing the example depicted in  FIG.  3   , a cursor  324  is shown selecting the “Person not recognized” interface element  322 . The cursor  324  in this and the following figures corresponds to a location of a touch of the associate  112  on a touchscreen device, selection using a mouse, and so forth. The user interface  116  presented on the associate device  114  may omit a visual representation of the cursor  324 . After selection of this interface element  322 , the image data  128  may be further processed with different computer vision algorithms to find the other person depicted in the image. Instead of this automated process, or in addition to it, the associate  112  may be presented with another user interface  116  to manually designate the user  102  who is not recognized and delineate them within the image data  128 . 
     In other implementations, other information may be presented within the image gallery section  304 . For example, a first name or last name of the user  102  depicted in each of the gallery images  320  may be presented. 
     By using the user interface  116 , the associate  112  may be able to quickly and easily provide associate input data  132  to the facility management system  118 . As a result, the facility management system  118  may be able to quickly maintain information about the operation of the facility and the actions of the users  102  therein. 
     In one implementation, the user interface  116  may be used to facilitate tracking of the user  102  within the facility. For example, in a crowded situation, the analysis module  126  may be unable to distinguish between different users  102 . The user interface  116  may be used to acquire associate input data  132  that is indicative of where in a given set of image data  128  individual users  102  are. In some implementations, the associate  112  may also provide information to identify the users  102  that are depicted in the given set of image data  128 . 
       FIG.  4    depicts an illustration  400  of the user interface  116  configured to acquire group data  134  about users  102  entering the facility, according to some implementations. The user interface  116  depicted here may be presented on the associate device  114  or on another computing device. 
     By way of illustration, and not necessarily as a limitation, the user interface  116  depicted in  FIG.  4    may be presented after the associate  112  has selected the “Person not recognized” interface element  322  described above in  FIG.  3   . 
     In some situations, the facility management system  118  may call upon the assistance of the associate  112  to determine the group data  134 . In this illustration, the presentation section  302  and the image gallery section  304  are depicted similar to those described above. In this illustration, the gallery images  320  within the image gallery section  304  are sorted left to right in descending order of confidence determined by an automated system. For example, the facility management system  118  may have determined that user “D” has a confidence value of 0.2 of being grouped with user “A”, a confidence value of 0.15 of being grouped with user “B”, and a confidence value of 0.05 of being grouped with user “C”. The gallery images  320 , or other portions of the user interface  116 , may be configured to act as interface elements  322 . For example, by touching or clicking on a particular gallery image  320 , the associate  112  may be able to select or deselect that user  102  as being a member of the group. 
     In some implementations, such as depicted here, predicted members of the group are determined by the facility management system  118  and may be indicated by way of a change of border color, other visual indicia, relative placement within the image gallery section  304 , and so forth. 
     The associate  112  may use the various image interface elements  310  to review the image data  128  associated with the entrance of these users  102 . The associate  112  may then provide input by activating one or more of the interface elements  322 . For example, if the associate  112  believes the user “D” is part of a group with user “A” (which has been pre-selected), the associate  112  may activate the submit interface element  322 . As a result, associate input data  132  indicative of this determination is sent from the associate device  114  to the facility management system  118  for further processing. Continuing the example, the group data  134  may be updated to confirm that user “A” and user “D” are members of the same group. 
     In one implementation, the user interface  116  may be used to generate group data  134  after sensor data is determined to exceed a threshold value during entry of the user  102 . The facility management system  118  may determine a count of scans of the same entry credential data  122  that are made within a predetermined period of time. For example, the count of scans may be indicative of the number of times the barcode sensors  108 ( 1 ) in the entry area  202  received the same entry credential data  122 . A low confidence event may be determined when the count of scans is greater than a threshold, such as one. For example, a group of users  102  may pass along the user device  110  such that each user  102  is able to scan the same entry credential data  122  and pass through the gate  106 . Responsive to the count of scans being greater than a threshold, the facility management system  118  may cause the display on the associate device  114  of the user interface  116  such as that depicted in  FIG.  4   . Group data  134  may then be obtained based on the associate input data  132  that is received. 
     In another implementation, the user interface  116  may be used to generate group data  134  after sensor data is determined to exceed a threshold value during entry of the user  102 . The gate  106  may determine a count of users  102  entering, and this information may be included in the lane data  124 . For example, the gate  106  may include one or more infrared emitters such as light emitting diodes and infrared detectors that are used to determine how many people have passed through the gate  106 . The system may be configured such that one person is expected to pass with each distinct scan of the entry credential data  122 . If two people pass through the gate  106  after a single scan of the entry credential data  122 , this may be indicative of tailgating. 
     The system may determine the first lane data  124 ( 1 ) is indicative of a count of users  102  entering with the same entry credential data  122  exceeds a threshold value. For example, two people have passed through the gate  106  after a single scan of the entry credential data  122 . Presence of a representation of one or more additional users  102  depicted in the first image data  128  may be determined. For example, the analysis module  126  may process the first image data  128 ( 1 ) to determine a count of the faces present at the lane  104  at the time corresponding to the acquisition of the lane data  124 . 
     Responsive to the determination of the count of users  102  using the same entry credential data  122  exceeds a threshold value, the facility management system  118  may cause the display on the associate device  114  of the user interface  116  such as that depicted in  FIG.  4   . Group data  134  may then be obtained based on the associate input data  132  that is received. For example, the associate  112  may generate associate input data  132  that is indicative of a group relationship between the first user  102 ( 1 ) and at least some of the one or more additional users  102  who passed through the gate  106  with the first user  102 ( 1 ). The identifier associated with the entry credential data  122  may then be associated with the users  102  in the group. 
     Other information may also be presented within the user interface  116 . In one implementation, a tailgate event indicator  402  may be presented that notifies the associate  112  that a possible tailgating event occurred at a particular lane  104 . The possible tailgating event may be generated based at least in part on the lane data  124  obtained from the gate  106 . For example, the tailgate event indicator  402  may comprise an icon such as a triangle with an exclamation point within. 
       FIG.  5    depicts an illustration  500  of the user interface  116  configured to acquire associate input data  132  usable to generate or confirm group data  134  about users  102  entering the facility, according to some implementations. For example, the associate  112  is queried by way of the user interface  116  about whom they believe is in a group. The user interface  116  depicted here may be presented to the associate  112  by the associate device  114  or on another computing device. 
     The user interface  116  may include the image interface elements  310  described above. For example, a time index control may present timeline data such as indicating the time at which the same set of entry credential data  122  was presented twice at the gate  106 . In this user interface  116 , the presented image  308  comprises an overhead view of at least a portion of the entry area  202 . Overlaid onto the presented image  308  may be other information such as lane indicia  502 , tracked path indicia  504 , and so forth. For example, the lane indicia  502  provides a visual indicator of each of the lanes  104  that are within the presented image  308 . This provides spatial cues that may assist the associate  112  in providing an answer to a query. The tracked path indicia  504  may comprise an indication of where a particular user  102  has been within the facility. For example, tracked path indicia  504  may resemble a trail of breadcrumbs that show which lane  104  the user  102  is proceeding from. 
     The presented image  308  also includes an overlay presenting information such as the designator indicia  312  and the identifier indicia  314 . The associate  112  may use one or more of the interface elements  322  to select which of the users  102  they believe are members of a single group. In this illustration, the associate  112  has determined that user&#39;s A and D are members of the same group, and has selected the appropriate interface elements  322  that correspond with the identifier indicia  314 . Once selected, activation indicia  506  are presented. For example, a checkmark may be displayed within each of the control buttons that correspond to selected identifier indicia  314 . 
     Following selection of one or more of the designator indicia  312  or the identifier indicia  314  using the interface elements  322 , output  508  may also be presented. For example, the output  508  in  FIG.  5    indicates there are currently two users  102  selected as being in a group. 
     Other controls may also be present within the user interface  116 . For example, a change bounding box interface element  322  may allow the associate  112  to change the boundaries associated with the designator indicia  312 . 
     As described above, in some implementations, the members of a group may be pre-selected based on a determination made by the facility management system  118 . For example, the user interface  116  may have been initially presented to the associate  112  depicting group data  134  indicative of the highest confidence value determined by the automated system, that of user “A” and user “B”. The associate  112  may then either confirm this or may modify based on their assessment of the information presented in the user interface  116 . 
     In some implementations, the image gallery section  304  (not shown here) may also be presented. For example, activation of an image interface element  310  may result in presentation of the image gallery section  304 . 
       FIG.  6    depicts an illustration  600  of the user interface  116  configured to acquire group data  134  about users  102  entering the facility, according to some implementations. The user interface  116  also presents information about an identified user  102 , according to some implementations. The user interface  116  depicted here may be presented by the associate device  114  or on another computing device. 
     In this illustration, the query is for the associate  102  to determine who is in a group. Depicted are two presented images  308 . The first presented image  308 ( 1 ) depicts image data  128  obtained from a camera arranged at an oblique angle relative to the users  102 , such that the faces of the users  102  are visible. The second presented image  308 ( 2 ) depicts image data  128  obtained from an overhead camera. 
     As described above, image interface elements  310  may be used to change the presentation of the presented images  308 . Also presented are the various interface elements  322  allowing the associate  112  to provide input indicative of the determination by the associate  112  as to who is in a group. Depicted in this figure is user account information  602 . For example, the user account information  602  may comprise a first name, surname, user name, registration picture, picture chain from a previous visit to the facility, and so forth, for a particular user  102 . The user account information  602  may be based at least in part on the entry credential data  122  that was presented by the user  102  at the gate  106 . 
     In some implementations, the image gallery section  304  (not shown here) may also be presented. For example, activation of an image interface element  310  may result in presentation of the image gallery section  304 . 
       FIG.  7    depicts an illustration  700  of the user interface  116  configured to acquire input used to determine group data  134  about users  102  entering the facility by drawing on an image of users  102 , according to some implementations. The user interface  116  depicted here may be presented by the associate device  114  or on another computing device. 
     As depicted here, the associate device  114  may include a touch sensitive display. The user interface  116  may display the presented image  308 . The associate  112  may use their finger, stylus, or other implement (represented here by the cursor  324 ) to draw a line  702  around the users  102  depicted in the presented image  308  that are deemed by the associate  112  to be members of a single group. The resulting associate input data  132  indicative of this grouping may then be provided to the facility management system  118 . In another implementation, the associate  112  may tap on a particular portion of the presented image  308 , such as a particular identifier indicia  314  or designator indicia  312  to select or deselect a user  102  from a group. 
     In some implementations, the image gallery section  304  (not shown here) may also be presented. For example, activation of an image interface element  310  may result in presentation of the image gallery section  304 . 
       FIG.  8    depicts an illustration  800  of the user interface  116  configured to acquire input used to determine group data  134  about users  102  entering the facility that also includes an image of the associate  112 , according to some implementations. The user interface  116  depicted here may be presented by the associate device  114  or on another computing device. 
     In this illustration, the associate  112  may select the members of a group directly within the presented image  308 . For example, the associate  112  may tap or circle the identifier indicia  314  to add or remove the associated user  102  to the group. 
     As depicted here, the presented image  308  may include the associate  112 . Inclusion of the associate  112  in the presented image  308  may provide cues that assist the associate  112  in answering a query. In some implementations, the apparent orientation of the presented image  308  and the user interface  116  may vary. For example, the presented image  308  may always be presented with north at the top of the display, such as depicted here. In another example, the presented image  308  may be oriented relative to a direction the associate  112  is facing. Identification data indicative of identification of the associate  112  may be accessed and used to cause display of one or more of an identifier indicia or a designator indicia indicative of the associate  112 . For example, the name of the associate  112  may be retrieved and presented as an overlay in the presented image  308 . 
     As described above, the user interface  116  may include other elements such as the image interface elements  310 , interface elements  322 , and so forth. In some implementations, the image gallery section  304  (not shown here) may also be presented. For example, activation of an image interface element  310  may result in presentation of the image gallery section  304 . 
       FIG.  9    depicts an illustration  900  of the user interface  116  configured to acquire input used to determine who of the users  102  has exited the facility, according to some implementations. 
     As users  102  exit the facility, the associate  112  may be queried to help determine who has left. In this illustration  900 , image data  128  obtained by image sensors  108 ( 2 ) covering the exit lanes  206  are displayed within the presentation section  302 . The image gallery section  304  may present gallery images  320 . For example, the gallery images  320  may comprise images obtained upon entry to the facility. By utilizing the interface elements  322 , the associate  112  may provide associate input data  132  to the facility management system  118  for further processing. 
     Information in the image gallery section  304  may be presented based on information available to the facility management system  118 . For example, gallery images  320  of users  102  who are believed to still be within the facility may be presented within the image gallery section  304 . Continuing the example, gallery images  320  of users  102  who have already been determined to have left the facility and not re-entered may be omitted from the image gallery section  304 . 
     As described above, in some implementations, the gallery images  320  selected for presentation within the image gallery section  304 , the order of presentation, and so forth, may be determined based at least in part on information maintained by the facility management system  118 . For example, the gallery images  320  may omit users  102  who are currently being tracked at a different location within the facility. In another example, gallery images  320  associated with the exit may be for those users  102  identified as being proximate to the exit lanes  206  at a particular time. 
     In one implementation, the exit lanes  206  may be configured to allow egress of the user  102  without further presentation of the user device  110 . For example, the gate  106  in the exit lane  206  may open upon the approach of the user  102 . 
     In another implementation, the gate  106  in the exit lane  206  may be configured to remain closed for a brief period of time and then open to allow the user  102  to pass. This brief period of time when the exit lane  206  is closed may allow for the acquisition of image data  128  that may be used to determine what users  102  have left the facility. 
     The facility management system  118  may receive lane data  124  indicative of passage of a user  102  at an exit lane  206  at a particular time. Tracking data may be accessed that is indicative of presence of the user  102  at the exit lane  206  at the particular time. For example, the tracking data may indicate that the location of the user  102  at the time immediately prior to the particular time was within a threshold distance of the exit lane  206  that generated the lane data  124 . The facility management system  118  may then generate exit data indicative of the user  102  who is associated with the identifier as having left the facility. Based on this exit data, the identifier is designated as no longer being present in the facility. 
     Illustrative Systems 
       FIG.  10    is a block diagram  1000  illustrating a materials handling facility (facility)  1002  using the system  100 , according to some implementations. A facility  1002  comprises one or more physical structures or areas within which one or more items  1004 ( 1 ),  1004 ( 2 ), . . . ,  1004 (Q) may be held. As used in this disclosure, letters in parenthesis such as “(Q)” indicate an integer value greater than or equal to zero. The items  1004  may comprise physical goods, such as books, pharmaceuticals, repair parts, electronic gear, and so forth. 
     The facility  1002  may include one or more areas designated for different functions with regard to inventory handling. In this illustration, the facility  1002  includes a receiving area  1006 , a storage area  1008 , and a transition area  1010 . 
     The receiving area  1006  may be configured to accept items  1004 , such as from suppliers, for intake into the facility  1002 . For example, the receiving area  1006  may include a loading dock at which trucks or other freight conveyances unload the items  1004 . In some implementations, the items  1004  may be processed, such as at the receiving area  1006 , to generate at least a portion of item data. The item data may comprise information about a particular item  1004 , such as size, shape, weight, color, stock keeping unit (SKU), and so forth. For example, an item  1004  may be imaged or otherwise scanned to develop reference images or representations of the item  1004  at the receiving area  1006 . 
     The storage area  1008  is configured to store the items  1004 . The storage area  1008  may be arranged in various physical configurations. In one implementation, the storage area  1008  may include one or more aisles  1012 . The aisle  1012  may be configured with, or defined by, inventory locations  1014  on one or both sides of the aisle  1012 . The inventory locations  1014  may include one or more of a hook, a shelf, a rack, a case, a cabinet, a bin, a floor location, or other suitable storage mechanisms for holding, supporting, or storing the items  1004 . For example, the inventory locations  1014  may comprise racks with hooks or shelves with lanes designated therein. The inventory locations  1014  may be affixed to the floor or another portion of the structure of the facility  1002 . The inventory locations  1014  may also be movable such that the arrangements of aisles  1012  may be reconfigurable. In some implementations, the inventory locations  1014  may be configured to move independently of an outside operator. For example, the inventory locations  1014  may comprise a rack with a power source and a motor, operable by a computing device to allow the rack to move from one location within the facility  1002  to another. 
     One or more users  102 ( 1 ),  102 ( 2 ), . . . ,  102 (U) and totes  1018 ( 1 ),  1018 ( 2 ), . . . ,  1018 (T) or other material handling apparatuses may move within the facility  1002 . For example, the user  102  may move about within the facility  1002  to pick or place the items  1004  in various inventory locations  1014 , placing them on the tote  1018  for ease of transport. The tote  1018  is configured to carry or otherwise transport one or more items  1004 . For example, the tote  1018  may be a basket, cart, bag, bin, and so forth. In other implementations, other material handling apparatuses such as robots, forklifts, cranes, aerial drones, and so forth, may move about the facility  1002  picking, placing, or otherwise moving the items  1004 . For example, a robot may pick an item  1004  from a first inventory location  1014 ( 1 ) and move the item  1004  to a second inventory location  1014 ( 2 ). 
     One or more sensors  108  may be configured to acquire information in the facility  1002 . The sensors  108  may include, but are not limited to, barcode sensors  108 ( 1 ) image sensors  108 ( 2 ), and so forth. The sensors  108  may be stationary or mobile, relative to the facility  1002 . The facility  1002  may include image sensors  108 ( 2 ) to obtain images of the user  102  or other objects in the facility  1002 . For example, stationary image sensors  108 ( 2 ) may be mounted to walls, ceilings, furniture, while mobile image sensors  108 ( 2 ) on the associate device  114  may be used. The sensors  108  may exhibit a field of view (FOV)  1016 . For example, the image sensors  108 ( 2 ) have a FOV  1016  within which they acquire images. The sensors  108  are discussed in more detail below with regard to  FIG.  11   . In another example, the inventory locations  1014  may contain weight sensors  108 ( 8 ) to acquire weight data of items  1004  stowed therein, image sensors  108 ( 2 ) to acquire images of picking or placement of items  1004 , and so forth. 
     While the storage area  1008  is depicted as having one or more aisles  1012 , inventory locations  1014  storing the items  1004 , sensors  108 , and so forth, it is understood that the receiving area  1006 , the transition area  1010 , or other areas of the facility  1002  may be similarly equipped. Furthermore, the arrangement of the various areas within the facility  1002  is depicted functionally rather than schematically. For example, in some implementations, multiple different receiving areas  1004 , storage areas  1006 , and transition areas  1008  may be interspersed rather than segregated in the facility  1002 . 
     The facility  1002  may include, or be coupled to, the facility management system  118 . The facility management system  118  is configured to interact with one or more of the users  102  or devices such as sensors  108 , robots, material handling equipment, computing devices, and so forth, in one or more of the receiving area  1006 , the storage area  1008 , or the transition area  1010 . 
     The facility management system  118  or other systems may use the sensor data to track the location of objects within the facility  1002 , movement of the objects, or provide other functionality. The sensor data may include but is not limited to lane data  124 , the image data  128 , and so forth. Objects may include, but are not limited to, items  1004 , users  102 , totes  1018 , and so forth. For example, a series of images acquired by the image sensor  108 ( 2 ) may indicate removal by the user  102  of an item  1004  from a particular location on the inventory location  1014  and placement of the item  1004  on or at least partially within the tote  1018 . 
     The facility  1002  may be configured to receive different kinds of items  1004  from various suppliers and to store them until a customer orders or retrieves one or more of the items  1004 . A general flow of items  1004  through the facility  1002  is indicated by the arrows of  FIG.  10   . Specifically, as illustrated in this example, items  1004  may be received from one or more suppliers, such as manufacturers, distributors, wholesalers, and so forth, at the receiving area  1006 . In various implementations, the items  1004  may include merchandise, commodities, perishables, or any suitable type of item  1004 , depending on the nature of the enterprise that operates the facility  1002 . 
     Upon being received from a supplier at the receiving area  1006 , the items  1004  may be prepared for storage in the storage area  1008 . For example, in some implementations, items  1004  may be unpacked or otherwise rearranged. The facility management system  118  may include one or more software applications executing on a computer system to provide inventory management functions. These inventory management functions may include maintaining information indicative of the type, quantity, condition, cost, location, weight, or any other suitable parameters with respect to the items  1004 . The items  1004  may be stocked, managed, or dispensed in terms of countable units, individual units, or multiple units, such as packages, cartons, crates, pallets, or other suitable aggregations. Alternatively, some items  1004 , such as bulk products, commodities, and so forth, may be stored in continuous or arbitrarily divisible amounts that may not be inherently organized into countable units. Such items  1004  may be managed in terms of a measurable quantity such as units of length, area, volume, weight, time, duration, or other dimensional properties characterized by units of measurement. Generally speaking, a quantity of an item  1004  may refer to either a countable number of individual or aggregate units of an item  1004  or a measurable amount of an item  1004 , as appropriate. 
     After arriving through the receiving area  1006 , items  1004  may be stored within the storage area  1008 . In some implementations, like items  1004  may be stored or displayed together in the inventory locations  1014  such as in bins, on hooks, on shelves, and so forth. In such an implementation, all items  1004  of a given kind are stored in one inventory location  1014 . In other implementations, like items  1004  may be stored in different inventory locations  1014 . For example, to optimize retrieval of certain items  1004  having frequent turnover within a large physical facility  1002 , those items  1004  may be stored in several different inventory locations  1014  to reduce congestion that might occur at a single inventory location  1014 . 
     When a customer order specifying one or more items  1004  is received, or as a user  102  progresses through the facility  1002 , the corresponding items  1004  may be selected or “picked” from the inventory locations  1014  containing those items  1004 . In various implementations, item picking may range from manual to completely automated picking. For example, in one implementation, a user  102  may have a list of items  1004  they desire and may progress through the facility  1002  picking items  1004  from inventory locations  1014  within the storage area  1008  and placing those items  1004  into a tote  1018 . In other implementations, employees of the facility  1002  may pick items  1004  using written or electronic pick lists derived from customer orders. These picked items  1004  may be placed into the tote  1018  as the employee progresses through the facility  1002 . 
     After items  1004  have been picked, the items  1004  may be processed at a transition area  1010 . The transition area  1010  may be any designated area within the facility  1002  where items  1004  are transitioned from one location to another or from one entity to another. For example, the transition area  1010  may be a packing station within the facility  1002 . When the item  1004  arrives at the transition area  1010 , the item  1004  may be transitioned from the storage area  1008  to the packing station. Information about the transition may be maintained by the facility management system  118 . 
     In another example, if the items  1004  are departing the facility  1002 , a list of the items  1004  may be obtained and used by the facility management system  118  to transition responsibility for, or custody of, the items  1004  from the facility  1002  to another entity. For example, a carrier may accept the items  1004  for transport with that carrier accepting responsibility for the items  1004  indicated in the list. In another example, a user  102  may purchase or rent the items  1004  and remove the items  1004  from the facility  1002 . During use of the facility  1002 , the user  102  may move about the facility  1002  to perform various tasks, such as picking or placing the items  1004  in the inventory locations  1014 . 
     The facility management system  118  may generate interaction data  1020 . The interaction data  1020  provides information about an interaction between the user  102  and an item  1004 , such as a pick of an item  1004  from the inventory location  1014 , a place of an item  1004  to the inventory location  1014 , a touch made to an item  1004  at the inventory location  1014 , a gesture associated with an item  1004  at the inventory location  1014 , and so forth. The interaction data  1020  may include one or more of the type of interaction, interaction location identifier indicative of where at the inventory location  1014  the interaction took place, item identifier, quantity change to the item  1004 , user identifier, and so forth. The interaction data  1020  may then be used to further update the item data. For example, the quantity of items  1004  on hand at a particular inventory location may be changed based on an interaction that picks or places one or more items  1004  at the inventory location  1014 . 
     The facility management system  118  may combine or otherwise utilize different types of data from different types of sensors  108 . For example, weight data obtained from weight sensors  108 ( 8 ) at the inventory location  1014  may be used instead of, or in conjunction with image data  128  to determine the interaction data  1020 . 
       FIG.  11    is a block diagram  1100  illustrating additional details of the facility  1002 , according to some implementations. The facility  1002  may be connected to one or more networks  1102 , which in turn connect to one or more servers  1104 . The network  1102  may include private networks such as an institutional or personal intranet, public networks such as the Internet, or a combination thereof. The network  1102  may utilize wired technologies (e.g., wires, fiber optic cables, and so forth), wireless technologies (e.g., radio frequency, infrared, acoustic, optical, and so forth), or other connection technologies. The network  1102  is representative of any type of communication network, including one or more of data networks or voice networks. The network  1102  may be implemented using wired infrastructure (e.g., copper cable, fiber optic cable, and so forth), a wireless infrastructure (e.g., cellular, microwave, satellite, and so forth), or other connection technologies. 
     The servers  1104  may be configured to execute one or more modules or software applications associated with the facility management system  118  or other systems. While the servers  1104  are illustrated as being in a location outside of the facility  1002 , in other implementations, at least a portion of the servers  1104  may be located at the facility  1002 . The servers  1104  are discussed in more detail below with regard to  FIG.  12   . 
     The users  102 , the totes  1018 , or other objects in the facility  1002  may be equipped with one or more tags  1106 . The tags  1106  may be configured to emit a signal  1108 . In one implementation, the tag  1106  may be a radio frequency identification (RFID) tag  1106  configured to emit a RF signal  1108  upon activation by an external signal. For example, the external signal may comprise a radio frequency signal or a magnetic field configured to energize or activate the RFID tag  1106 . In another implementation, the tag  1106  may comprise a transmitter and a power source configured to power the transmitter. For example, the tag  1106  may comprise a Bluetooth Low Energy (BLE) transmitter and battery. In other implementations, the tag  1106  may use other techniques to indicate presence of the tag  1106 . For example, an acoustic tag  1106  may be configured to generate an ultrasonic signal  1108 , which is detected by corresponding acoustic receivers. In yet another implementation, the tag  1106  may be configured to emit an optical signal  1108 . 
     The facility management system  118  may be configured to use the tags  1106  for one or more of identification of the object, determining a location of the object, and so forth. For example, the users  102  may wear tags  1106 , the totes  1018  may have tags  1106  affixed, and so forth, which may be read and, based at least in part on signal strength, used to determine identity and location. 
     Generally, the facility management system  118  or other systems associated with the facility  1002  may include any number and combination of input components, output components, and servers  1104 . 
     The one or more sensors  108  may be arranged at one or more locations within the facility  1002 . For example, the sensors  108  may be mounted on or within a floor, wall, at a ceiling, at an inventory location  1014 , on a tote  1018 , may be carried or worn by a user  102 , and so forth. 
     The sensors  108  may include one or more barcode sensors  108 ( 1 ). The barcode sensors  108 ( 1 ) may be configured to read an optical machine-readable code. The barcode sensors  108 ( 1 ) may comprise a camera or other image sensor, laser scanner, photodetector array, and so forth. For example, the barcode sensor  108 ( 1 ) may comprise the LSR116 or LSR118 unit produced by Access Limited of Reading, United Kingdom. 
     The sensors  108  may include one or more image sensors  108 ( 2 ). The one or more image sensors  108 ( 2 ) may include cameras configured to acquire images of a scene. The image sensors  108 ( 2 ) are configured to detect light in one or more wavelengths including, but not limited to, terahertz, infrared, visible, ultraviolet, and so forth. The image sensors  108 ( 2 ) may comprise charge coupled devices (CCD), complementary metal oxide semiconductor (CMOS) devices, microbolometers, and so forth. The facility management system  118  may use image data  128  acquired by the image sensors  108 ( 2 ) during operation of the facility  1002 . For example, the facility management system  118  may identify items  1004 , users  102 , totes  1018 , and so forth, based at least in part on their appearance within the image data  128  acquired by the image sensors  108 ( 1 ). The image sensors  108 ( 2 ) may be mounted in various locations within the facility  1002 . For example, image sensors  108 ( 2 ) may be mounted overhead, on inventory locations  1014 , may be worn or carried by users  102 , may be affixed to totes  1018 , and so forth. 
     One or more depth sensors  108 ( 3 ) may also be included in the sensors  108 . The depth sensors  108 ( 3 ) may be used to acquire distance data, spatial or three-dimensional (3D) data, and so forth, about objects within a sensor FOV  1016 . The depth sensors  108 ( 3 ) may include optical time-of-flight systems, range cameras, lidar systems, sonar systems, radar systems, structured light systems, stereo vision systems, optical interferometry systems, and so forth. 
     The facility management system  118  may use the distance data acquired by the depth sensors  108 ( 3 ) to determine a distance to an object, identify an object, determine a location of an object in 3D real space, and so forth. For example, the distance data or depth data provided by an optical time-of-flight sensor may indicate the presence of a user&#39;s  102  hand near a particular inventory location  1014 . 
     One or more switches  108 ( 4 ) may be used to acquire information. The switches  108 ( 4 ) may be used to accept input from the user  102 , detect contact with an inventory location  1014 , and so forth. The switches  108 ( 4 ) may comprise mechanical, capacitive, optical, or other mechanisms. The facility management system  118  may use data from the switches  108 ( 4 ) to generate event data. 
     The sensors  108  may include capacitive sensors  108 ( 5 ). Circuitry associated with the capacitive sensor  108 ( 5 ) generates capacitance data. The capacitive sensor  108 ( 5 ) may comprise one or more conductive elements and a capacitive sensor module that includes electronics to determine the capacitance of a conductive element. The capacitive sensors  108 ( 5 ) may be configured to utilize a far-field capacitance effect. The far-field capacitance effect may be determined by measuring the self-capacitance of the conductive elements, rather than a mutual capacitance. In one implementation, a known charge may be provided to the conductive element, and the resultant voltage may be measured between the conductive element and the ground. A shield comprising an electrical conductor may be arranged along one or more sides of the conductive element. For example, the shield may be separated from the conductive element by an electrical insulator. During operation, the shield may be driven to the same (or a substantially similar) electrical potential as that provided to the conductive element. As a result of this, a voltage difference that is below a threshold voltage results between the shield and the conductive element. In some implementations, the voltage difference may be zero. The shield in this configuration directs the electric field generally away from the shield. This directionality may be used to prevent erroneous readings for objects on the back side of the conductive element, which may occur in an unshielded configuration. The directionality may also be used to provide a desired sensor FOV  1016 . In some implementations, a ground plane may be arranged behind the shield, opposite the conductive element. The ground plane may be separated from the shield by an electrical insulator. The ground plane may be connected to an earth ground in some implementations. Proximity of an object to the conductive element or contact by the object with the conductive element affects the charge on the conductive element, producing a change in the resultant voltage that may then be measured and used to determine a capacitance value. 
     The sensors  108  may include one or more touch sensors  108 ( 6 ). The touch sensors  108 ( 6 ) may use resistive, capacitive, surface capacitance, projected capacitance, mutual capacitance, optical, Interpolating Force-Sensitive Resistance (IFSR), or other mechanisms to determine the position of a touch or near-touch. For example, the IFSR may comprise a material configured to change electrical resistance responsive to an applied force. The location within the material of that change in electrical resistance may indicate the position of the touch. The facility management system  118  may use data from the touch sensors  108 ( 6 ) to receive information from the user  102 . For example, the touch sensor  108 ( 6 ) may be integrated with the tote  1018  to provide a touchscreen with which the user  102  may select from a menu one or more particular items  1004  for picking, enter a manual count of items  1004  at an inventory location  1014 , and so forth. In some implementations, the touch sensors  108 ( 6 ) may provide information indicative of a fingerprint of a person, such as the user  102 . This information may be used to identify the person. 
     One or more microphones  108 ( 7 ) may be configured to acquire information indicative of sound present in the environment. In some implementations, arrays of microphones  108 ( 7 ) may be used. These arrays may implement beamforming techniques to provide for directionality of gain. The facility management system  118  may use the one or more microphones  108 ( 7 ) to acquire information from acoustic tags  1106 , accept voice input from the users  102 , determine ambient noise level, determine location of the user  102  within the facility  1002 , and so forth. 
     The sensors  108  may include one or more weight sensors  108 ( 8 ) that are configured to measure the weight of a load, such as the item  1004 , the tote  1018 , or other objects. The weight sensors  108 ( 8 ) may be configured to measure the weight of the load at one or more of the inventory locations  1014 , the tote  1018 , on the floor of the facility  1002 , and so forth. For example, the inventory location  1014  may include a plurality of hooks, lanes, or platforms, with one or more weight sensors  108 ( 8 ) to provide weight data about an individual hook, lane, or platform. The weight sensors  108 ( 8 ) may include one or more sensing mechanisms to determine the weight of a load. These sensing mechanisms may include piezoresistive devices, piezoelectric devices, capacitive devices, electromagnetic devices, optical devices, potentiometric devices, microelectromechanical devices, and so forth. The sensing mechanisms of weight sensors  108 ( 8 ) may operate as transducers that generate one or more signals based on an applied force, such as that of the load due to gravity. For example, the weight sensor  108 ( 8 ) may comprise a load cell having a strain gauge and a structural member that deforms slightly when weight is applied. By measuring a change in the electrical characteristic of the strain gauge, such as capacitance or resistance, the weight may be determined. In another example, the weight sensor  108 ( 8 ) may comprise a force sensing resistor (FSR). The FSR may comprise a resilient material that changes one or more electrical characteristics when compressed. For example, the electrical resistance of a particular portion of the FSR may decrease as the particular portion is compressed by an applied mechanical force. The facility management system  118  may use the data acquired by the weight sensors  108 ( 8 ) to identify an object, determine a change in the quantity of objects, determine a location of an object, maintain shipping records, and so forth. 
     The sensors  108  may include one or more light sensors  108 ( 9 ). The light sensors  108 ( 9 ) may be configured to provide photodetector data indicative of one or more of color or intensity of light impinging thereupon. For example, the light sensor  108 ( 9 ) may comprise a photodiode and associated circuitry configured to generate a signal or data indicative of an incident flux of photons. The light sensors  108 ( 9 ) may be sensitive to one or more of infrared light, visible light, or ultraviolet light. For example, the light sensors  108 ( 9 ) may be sensitive to infrared light, and infrared light sources such as light emitting diodes (LEDs) may provide illumination. The light sensors  108 ( 9 ) may include photodiodes, photoresistors, photovoltaic cells, quantum dot photoconductors, bolometers, pyroelectric infrared detectors, and so forth. For example, the light sensor  108 ( 9 ) may use germanium photodiodes to detect infrared light. 
     One or more radio frequency identification (RFID) readers  108 ( 10 ), near field communication (NFC) systems, and so forth, may be included as sensors  108 . For example, the RFID readers  108 ( 10 ) may be configured to read the RF tags  1106 . Information acquired by the RFID reader  108 ( 10 ) may be used by the facility management system  118  to identify an object associated with the RF tag  1106  such as the item  1004 , the user  102 , the tote  1018 , and so forth. For example, based on information from the RFID readers  108 ( 10 ) detecting the RF tag  1106  at different times and RFID readers  108 ( 10 ) having different locations in the facility  1002 , a velocity of the RF tag  1106  may be determined. In another example, the RFID readers  108 ( 10 ) may receive the entry credential data  122  from the user device  110 . 
     One or more RF receivers  108 ( 11 ) may also be included as sensors  108 . In some implementations, the RF receivers  108 ( 11 ) may be part of transceiver assemblies. The RF receivers  108 ( 11 ) may be configured to acquire RF signals  1108  associated with Wi-Fi, Bluetooth, ZigBee, 4G, 3G, LTE, or other wireless data transmission technologies. The RF receivers  108 ( 11 ) may provide information associated with data transmitted via radio frequencies, signal strength of RF signals  1108 , and so forth. For example, information from the RF receivers  108 ( 11 ) may be used by the facility management system  118  to determine a location of an RF source, such as a communication interface onboard the tote  1018 . In another example, the RF receivers  108 ( 11 ) may receive entry credential data  122  from the user device  110 . 
     The sensors  108  may include one or more accelerometers  108 ( 12 ), which may be worn or carried by the user  102 , mounted to the tote  1018 , included in the associate device  114 , and so forth. The accelerometers  108 ( 12 ) may provide information such as the direction and magnitude of an imposed acceleration. Data such as rate of acceleration, determination of changes in direction, speed, and so forth, may be determined using the accelerometers  108 ( 12 ). 
     A gyroscope  108 ( 13 ) may provide information indicative of rotation of an object affixed thereto. For example, the associate device  114  may be equipped with a gyroscope  108 ( 13 ) to provide data indicative of orientation of the associate device  114 . 
     A magnetometer  108 ( 14 ) may be used to determine an orientation by measuring ambient magnetic fields, such as the terrestrial magnetic field. The magnetometer  108 ( 14 ) may be worn or carried by the user  102 , mounted to another device, and so forth. For example, the magnetometer  108 ( 14 ) mounted to the associate device  114  may act as a compass and provide information indicative of which direction the associate device  114  is oriented. In another example, a magnetometer  108 ( 14 ) in the user device  110  may detect particular magnetic fields in the entry area  202 . Information about these magnetic fields may then be used to determine that the user device  110  has passed through the entry area  202 . 
     The sensors  108  may include proximity sensors  108 ( 15 ) used to determine presence of an object, such as the user  102 , the tote  1018 , and so forth. The proximity sensors  108 ( 15 ) may use optical, electrical, ultrasonic, electromagnetic, or other techniques to determine a presence of an object. In some implementations, the proximity sensors  108 ( 15 ) may use an optical emitter and an optical detector to determine proximity. For example, an optical emitter may emit light, a portion of which may then be reflected by the object back to the optical detector to provide an indication that the object is proximate to the proximity sensor  108 ( 15 ). In other implementations, the proximity sensors  108 ( 15 ) may comprise a capacitive proximity sensor  108 ( 15 ) configured to provide an electrical field and determine a change in electrical capacitance due to presence or absence of an object within the electrical field. 
     The proximity sensors  108 ( 15 ) may be configured to provide sensor data indicative of one or more of a presence or absence of an object, a distance to the object, or characteristics of the object. An optical proximity sensor  108 ( 15 ) may use time-of-flight (ToF), structured light, interferometry, or other techniques to generate the distance data. For example, an optical time-of-flight sensor determines a propagation time (or “round-trip” time) of a pulse of emitted light from an optical emitter or illuminator that is reflected or otherwise returned to an optical detector. By dividing the propagation time in half and multiplying the result by the speed of light in air, the distance to an object may be determined. In another implementation, a structured light pattern may be provided by the optical emitter. A portion of the structured light pattern may then be detected on the object using a sensor  108  such as an image sensor  108 ( 2 ). Based on an apparent distance between the features of the structured light pattern, the distance to the object may be calculated. Other techniques may also be used to determine distance to the object. In another example, the color of the reflected light may be used to characterize the object, such as skin, clothing, tote  1018 , and so forth. 
     The sensors  108  may also include an instrumented auto-facing unit (IAFU)  108 ( 16 ). The IAFU  108 ( 16 ) may comprise a position sensor configured to provide data indicative of displacement of a pusher. As an item  1004  is removed from the IAFU  108 ( 16 ), the pusher moves, such as under the influence of a spring, and pushes the remaining items  1004  in the IAFU  108 ( 16 ) to the front of the inventory location  1014 . By using data from the position sensor, and given item data such as a depth of an individual item  1004 , a count may be determined, based on a change in position data. For example, if each item  1004  is 1 inch deep and the position data indicates a change of 11 inches, the quantity held by the IAFU  108 ( 16 ) may have changed by 11 items  1004 . This count information may be used to confirm or provide a cross check for a count obtained by other means, such as analysis of the weight data, the image data  128 , and so forth. 
     The sensors  108  may include other sensors  108 (S) as well. For example, the other sensors  108 (S) may include light curtains, ultrasonic rangefinders, thermometers, barometric sensors, hygrometers, biometric sensors, and so forth. For example, the facility management system  118  may use information from biometric sensors such as fingerprint readers, hand readers, iris readers, and so forth, to identify the user  102 , the associate  112 , or other people in the facility  1002 . 
     In one implementation, a light curtain may utilize a linear array of light emitters and a corresponding linear array of light detectors. For example, the light emitters may comprise a line of infrared LEDs or vertical cavity surface emitting lasers (VCSELs) that are arranged above and in front of the inventory location  1014 , while the light detectors comprise a line of photodiodes sensitive to infrared light arranged below the light emitters. The light emitters produce a “lightplane” or sheet of infrared light that is then detected by the light detectors. An object passing through the lightplane may decrease the amount of light falling upon the light detectors. For example, the hand of the user  102  crossing this lightplane would prevent at least some of the light from light emitters from reaching a corresponding light detector. As a result, a position of the object along the linear array may be determined that is indicative of a touchpoint. This position may be expressed as touchpoint data, with the touchpoint being indicative of the intersection between the hand of the user  102  and the sheet of infrared light. In some implementations, a pair of light curtains may be arranged at right angles relative to one another to provide two-dimensional touchpoint data indicative of a position of touch in a plane. Input from the light curtain, such as indicating occlusion from a hand of a user  102  may be used to generate event data. 
     In some implementations, the image sensor  108 ( 2 ) or other sensors  108 (S) may include hardware processors, memory, and other elements configured to perform various functions. For example, the image sensors  108 ( 2 ) may be configured to generate image data  128 , send the image data  128  to another device such as the server  1104 , and so forth. 
     The facility  1002  may include one or more access points  1110  configured to establish one or more wireless networks. The access points  1110  may use Wi-Fi, NFC, Bluetooth, or other technologies to establish wireless communications between a device and the network  1102 . The wireless networks allow the devices to communicate with one or more of the sensors  108 , the facility management system  118 , the tag  1106 , a communication device of the tote  1018 , or other devices. 
     Output devices  1112  may also be provided in the facility  1002 . The output devices  1112  are configured to generate signals, which may be perceived by the user  102  or detected by the sensors  108 . 
     Haptic output devices  1112 ( 1 ) are configured to provide a signal that results in a tactile sensation to the user  102 . The haptic output devices  1112 ( 1 ) may use one or more mechanisms such as electrical stimulation or mechanical displacement to provide the signal. For example, the haptic output devices  1112 ( 1 ) may be configured to generate a modulated electrical signal, which produces an apparent tactile sensation in one or more fingers of the user  102 . In another example, the haptic output devices  1112 ( 1 ) may comprise piezoelectric or rotary motor devices configured to provide a vibration, which may be felt by the user  102 . 
     One or more audio output devices  1112 ( 2 ) may be configured to provide acoustic output. The acoustic output includes one or more of infrasonic sound, audible sound, or ultrasonic sound. The audio output devices  1112 ( 2 ) may use one or more mechanisms to generate the acoustic output. These mechanisms may include, but are not limited to, the following: voice coils, piezoelectric elements, magnetostrictive elements, electrostatic elements, and so forth. For example, a piezoelectric buzzer or a speaker may be used to provide acoustic output. 
     The display output devices  1112 ( 3 ) may be configured to provide output, which may be seen by the user  102  or detected by a light-sensitive sensor such as an image sensor  108 ( 2 ) or a light sensor  108 ( 9 ). In some implementations, the display output devices  1112 ( 3 ) may be electronically controlled to produce output in one or more of infrared, visible, or ultraviolet light. The output may be monochrome or in color. The display output devices  1112 ( 3 ) may be one or more of emissive, reflective, microelectromechanical, and so forth. An emissive display output device  1112 ( 3 ), such as using LEDs, electroluminescent elements, quantum dots, and so forth, is configured to emit light during operation. In comparison, a reflective display output device  1112 ( 3 ), such as using an electrophoretic or interferometric element, relies on ambient light to present an image. Backlights or front lights may be used to illuminate non-emissive display output devices  1112 ( 3 ) to provide visibility of the output in conditions where the ambient light levels are low. In some implementations, the display output devices  1112 ( 3 ) may comprise pre-printed tags, labels, and so forth. 
     Other output devices  1112 (T) may also be present. For example, the other output devices  1112 (T) may include scent/odor dispensers, document printers, 3D printers or fabrication equipment, and so forth. 
     One or more of the sensors  108 , one or more of the output devices  1112 , or both may be included in the user device  110 , associate device  114 , or other computing devices. The sensors  108  may be used as input devices on the user device  110 , the associate device  114 , or other computing devices. For example, a display output device  1112 ( 3 ) such as an LED display may be combined with a touch sensor  108 ( 6 ) to provide a touchscreen. The user interface  116  including image interface elements  310 , interface elements  322 , or other interface elements may be presented on the display output device  1112 ( 3 ). When a person touches the touchscreen, a signal is generated by the touch sensor  108 ( 6 ) and data is generated indicative of the position of the touch. The position of the touch is then associated with the position of the interface element  322  presented on the display output device  1112 ( 3 ). For example, the touch sensor  108 ( 6 ) may report a touch at coordinates ( 207 ,  195 ). Software executing on the computing device may associate the touch at coordinates ( 207 ,  195 ) with coordinates on the display output device  1112 ( 3 ) of ( 657 ,  598 ). These coordinates on the display output device  1112 ( 3 ) of ( 657 ,  598 ) may be determined to be within the boundary of an interface element  322  that looks like a button. Based on this determination, one or more computer-executable instructions assigned to the interface element  322  may be executed. For example, the instructions may result in generating data indicative of selection of the button. 
       FIG.  12    illustrates a block diagram  1200  of a server  1104  configured to support operation of the facility  1002 , according to some implementations. The server  1104  may be physically present at the facility  1002 , may be accessible by the network  1102 , or a combination of both. The server  1104  does not require end-user knowledge of the physical location and configuration of the system that delivers the services. Common expressions associated with the server  1104  may include “on-demand computing”, “software as a service (SaaS)”, “platform computing”, “network-accessible platform”, “cloud services”, “data centers”, and so forth. Services provided by the server  1104  may be distributed across one or more physical or virtual devices. 
     One or more power supplies  1202  may be configured to provide electrical power suitable for operating the components of the server  1104 . The one or more power supplies  1202  may comprise batteries, capacitors, fuel cells, photovoltaic cells, wireless power receivers, conductive couplings suitable for attachment to an external power source such as provided by an electric utility, and so forth. The server  1104  may include one or more hardware processors  1204  (processors) configured to execute one or more stored instructions. The processors  1204  may comprise one or more cores. One or more clocks  1206  may provide information indicative of date, time, ticks, and so forth. For example, the processor  1204  may use data from the clock  1206  to associate a particular interaction with a particular point in time. 
     The server  1104  may include one or more communication interfaces  1208  such as input/output (I/O) interfaces  1210 , network interfaces  1212 , and so forth. The communication interfaces  1208  enable the server  1104 , or components thereof, to communicate with other devices or components. The communication interfaces  1208  may include one or more I/O interfaces  1210 . The I/O interfaces  1210  may comprise Inter-Integrated Circuit (I2C), Serial Peripheral Interface bus (SPI), Universal Serial Bus (USB) as promulgated by the USB Implementers Forum, RS-232, and so forth. 
     The I/O interface(s)  1210  may couple to one or more I/O devices  1214 . The I/O devices  1214  may include input devices such as one or more of a sensor  108 , keyboard, mouse, touch sensor  108 ( 6 ), scanner, and so forth. The I/O devices  1214  may also include output devices  1112  such as one or more of a display output device  1112 ( 3 ), printer, audio speakers, and so forth. In some embodiments, the I/O devices  1214  may be physically incorporated with the server  1104  or may be externally placed. 
     The network interfaces  1212  may be configured to provide communications between the server  1104  and other devices, such as the totes  1018 , routers, access points  1110 , and so forth. The network interfaces  1212  may include devices configured to couple to personal area networks (PANS), local area networks (LANs), wireless local area networks (WLANS), wide area networks (WANs), and so forth. For example, the network interfaces  1212  may include devices compatible with Ethernet, Wi-Fi, Bluetooth, ZigBee, and so forth. 
     The server  1104  may also include one or more busses or other internal communications hardware or software that allow for the transfer of data between the various modules and components of the server  1104 . 
     As shown in  FIG.  12   , the server  1104  includes one or more memories  1216 . The memory  1216  may comprise one or more non-transitory computer-readable storage media (CRSM). The CRSM may be any one or more of an electronic storage medium, a magnetic storage medium, an optical storage medium, a quantum storage medium, a mechanical computer storage medium, and so forth. The memory  1216  provides storage of computer-readable instructions, data structures, program modules, and other data for the operation of the server  1104 . A few example functional modules are shown stored in the memory  1216 , although the same functionality may alternatively be implemented in hardware, firmware, or as a system on a chip (SoC). 
     The memory  1216  may include at least one operating system (OS) module  1218 . The OS module  1218  is configured to manage hardware resource devices such as the I/O interfaces  1210 , the I/O devices  1214 , the communication interfaces  1208 , and provide various services to applications or modules executing on the processors  1204 . The OS module  1218  may implement a variant of the FreeBSD operating system as promulgated by the FreeBSD Project; other UNIX or UNIX-like variants; a variation of the Linux operating system as promulgated by Linus Torvalds; the Windows operating system from Microsoft Corporation of Redmond, Wash., USA; and so forth. 
     Also stored in the memory  1216  may be a data store  1220  and one or more of the following modules. These modules may be executed as foreground applications, background tasks, daemons, and so forth. The data store  1220  may use a flat file, database, linked list, tree, executable code, script, or other data structure to store information. In some implementations, the data store  1220  or a portion of the data store  1220  may be distributed across one or more other devices including the servers  1104 , network attached storage devices, and so forth. 
     A communication module  1222  may be configured to establish communications with one or more of the associate devices  114 , the totes  1018 , the sensors  108 , other servers  1104 , or other devices. The communications may be authenticated, encrypted, and so forth. 
     The memory  1216  may store a facility management module  1224 . The facility management module  1224  is configured to provide the inventory functions as described herein with regard to the facility management system  118 . For example, the facility management module  1224  may track users  102  within the facility  1002 , maintain information about their grouping, track movement of items  1004  as they are picked or placed by the user  102 , and so forth. 
     The facility management module  1224  may include one or more of a data acquisition module  1226 , the interface module  120 , the analysis module  126 , and so forth. The data acquisition module  1226  may be configured to acquire and access information associated with operation of the facility  1002 . For example, the data acquisition module  1226  may acquire sensor data  1230  such as the lane data  124  from the gate  106 , the image data  128  from the image sensors  108 ( 2 ), and so forth. The sensor data  1230  may be accessed by the other modules for use. 
     The interface module  120  may operate as described above to allow the facility management system  118  to interact with other devices. The data store  1220  may store at least a portion of the entry credential data  122 , the presentation data  130 , the associate input data  132 , and so forth. 
     The analysis module  126  may be configured to use information such as one or more of the physical layout data  1228 , item data, sensor data  1230 , and so forth, to generate information such as tracking data  1232 , event data, the interaction data  1020 , and so forth. 
     The physical layout data  1228  may provide information indicative of where sensors  108  and inventory locations  1014  are in the facility  1002  with respect to one another, FOV  1016  of sensors  108  relative to the inventory location  1014 , and so forth. For example, the physical layout data  1228  may comprise information representative of a map or floor plan of the facility  1002  with relative positions of inventory locations  1014 , planogram data indicative of how items  1004  are to be arranged at the inventory locations  1014 , and so forth. 
     The physical layout data  1228  may associate a particular inventory location ID with other information such as physical location data, sensor position data, sensor direction data, sensor identifiers, and so forth. The physical location data provides information about where in the facility  1002  objects are, such as the inventory location  1014 , the sensors  108 , and so forth. In some implementations, the physical location data may be relative to another object. For example, the physical location data may indicate that a particular weight sensor  108 ( 8 ) or image sensor  108 ( 2 ) is associated with a particular inventory location  1014 . 
     The tracking data  1232  may comprise information indicative of a location with respect to the facility  1002  and a time of that location for a particular object. For example, the tracking data  1232  may comprise a time series of location data and timestamps for a particular user  102 . The tracking data  1232  may be determined using the sensor data  1230 . For example, the image data  128  may be processed by computer vision algorithms that perform image-based blob tracking, where the blob in the image is that of the user  102 , tote  1018 , or other object. The blob is a representation of an object being tracked in the image data, but need not be recognized as a particular thing. For example, the image-based blob tracking follows a cluster of pixels as they move about within an image, without resorting to object recognition to determine if that cluster of pixels is a user  102 , tote, and so forth. In other implementations other image-based tracking may also be used. For example, the object may be recognized as a particular human face, and may be subsequently tracked as such. The image-based tracking accesses a plurality of images obtained from a plurality of cameras to determine a location within the facility of the user  102 . Given the known location of a particular camera, known orientation of the camera, optical characteristics, or other information and the relative position of the object within the image data acquired from each camera, the location of the object may be determined. 
     The event data may comprise information indicative of a change deemed to be significant that is associated with an inventory location  1014  or portion thereof. For example, the event data may be indicative of a determination by a capacitive sensor  108 ( 5 ) of proximity of an object, such as an item  1004  or user  102 . In another example, the event data may comprise an indication that a weight change has exceeded a threshold value. In yet another example, the event data may indicate that motion between a plurality of images has been detected that exceeds a threshold value. The analysis module  126  may utilize one or more filter functions, comparison functions, and so forth, to determine the event data. For example, the event data may result from a determination that the capacitance data and weight data have each experienced changes that exceed respective threshold values. The analysis module  126  may utilize various rules or conditions to determine the occurrence of an event and subsequent generation of event data. 
     The analysis module  126  may also accept as input other sensor data  1230 , such as input from a light sensor  108 ( 9 ), accelerometer  108 ( 12 ), RF receiver  108 ( 11 ), and so forth. The analysis module  126  may process the sensor data  1230  using various techniques. For example, the image data  128  may be processed to generate information indicative of changes between images, object recognition data, determine the presence of a person, track an object, and so forth. For example, the generation of the designator indicia  312  may be performed at least in part by the analysis module  126  by processing at least a portion of the image data  128  with one or more computer vision algorithms to detect the presence of a person, or portion thereof such as the face of the user  102 . 
     Processing of one or more of the image data  128  or portions thereof may be performed by implementing, at least in part, one or more of the following tools or techniques. In one implementation, processing of the image data  128  may be performed, at least in part, using one or more tools available in the OpenCV library as developed by Intel Corporation of Santa Clara, Calif., USA; Willow Garage of Menlo Park, Calif., USA; and Itseez of Nizhny Novgorod, Russia, with information available at www.opencv.org. In another implementation, functions available in the OKAO machine vision library as promulgated by Omron Corporation of Kyoto, Japan, may be used to process the image data  128 . In still another implementation, functions such as those in the Machine Vision Toolbox for Matlab (MVTB) available using MATLAB as developed by MathWorks, Inc. of Natick, Mass., USA, may be utilized. 
     Techniques such as artificial neural networks (ANNs), active appearance models (AAMs), active shape models (ASMs), principal component analysis (PCA), cascade classifiers, and so forth, may also be used to process the sensor data  1230  or other data. For example, the ANN may be trained using a supervised learning algorithm such that object identifiers are associated with images of particular objects within training images provided to the ANN. Once trained, the ANN may be provided with the sensor data  1230  and the item data to allow for a determination of similarity between two or more images. 
     The analysis module  126  may generate the interaction data  1020 . The interaction data  1020  may include information indicative of a particular inventory location  1014  at which some activity has taken place, such as a pick or place of an item  1004 . Location information for an interaction may indicate a particular inventory location, coordinates of the point or area at an inventory location  1014  that includes several hooks, and so forth. The interaction may comprise movement, presence, pick, place, and so forth, of an object or an item  1004 . For example, a location associated with a pick may be determined by using tracking data  1232  to determine a particular user  102  is present at a particular inventory location  1014 . 
     The analysis module  126  may be configured to generate group data  134 . For example, the analysis module  126  may use computer vision techniques, ANNs, and so forth, to attempt to determine if two or more users  102  are members of a common group. As described above, in some implementations, the results of this automated process may be unavailable or may be associated with a confidence value that is below a threshold. For example, an automated determination of a group may be suggestive, but considered unreliable by itself. 
     The group data  134  may include or be based at least in part on one or more of predicted group data  1234  or final group data  1236 . The analysis module  126  may generate predictive group data  1234  without human intervention. The predicted group data  1234  may comprise the automated system&#39;s determined assessment as to the membership of a group. The predicted group data  1234  may be based at least in part on one or more of: determined physical distance in the facility  1002  between a first user  102 ( 1 ) and a second user  102 ( 2 ), determined resemblance between the first user  102 ( 1 ) and the second user  102 ( 2 ), sequential entry of the first user  102 ( 1 ) and the second user  102 ( 2 ) at the facility  1002 , entry credential data  122  obtained from the first user  102 ( 1 ) and the second user  102 ( 2 ) during entry to the facility  1002 , and so forth. For example, the analysis module  126  may determine metrics that are descriptive of the faces of two users  102 . When the variance between those metrics is less than or equal to a threshold value, the two users  102  may be deemed to resemble one another. For example, siblings may resemble one another. In another implementation, resemblance may be based at least in part on the similarity of colors worn. For example, a group of users  102  that are in uniform and enter consecutively may be determined to be members of the group. In another example, the predicted group data  1234  may be generated by grouping users  102  who exhibit a relative distance from each other that is less than a threshold distance. In another example, the predicted group data  1234  may be generated by determining if two users  102  are in contact with one another, such as holding hands. 
     The final group data  1236  may comprise what the facility management system  118  had deemed to be indicative of a grouping between users  102 . For example, where the predicted group data  1234  is above a threshold confidence value, the predicted group data  1234  may be used as the final group data  1236 . In another example, where the predicted group data  1234  is below the threshold confidence value, associate input data  132  may be obtained using user interfaces  116  described above. Based on this associate input data  132 , final group data  1236  may be determined. For example, the final group data  1236  may comprise the information specified by the associate input data  132 . 
     The facility management module  1224 , and modules associated therewith, may access sensor data  1230 , threshold data, and so forth. The threshold data may comprise one or more thresholds, ranges, percentages, and so forth, that may be used by the various modules in operation. For example, the analysis module  126  may access threshold data to determine if a confidence value of a determination of identification, grouping, and so forth, necessitates the use of the associate  112 . 
     The facility management module  1224  may generate output data. For example, the output data may include the interaction data  1020 , inventory levels for individual types of items  1004 , overall inventory of the facility  1002 , and so forth. 
     Other modules  1238  may also be present in the memory  1216  as well as other data  1240  in the data store  1220 . For example, the other modules  1238  may include an accounting module while the other data  1240  may include billing data. The accounting module may be configured to assess charges to accounts associated with particular users  102  or other entities based on interaction data indicative of picks and places of item  1004   s , while the billing data may include information such as payment account numbers. 
     The associate device  114  may comprise a computing device with one or more of the elements described above with regard to the server  1104 . For example, the associate device  114  may comprise a power supply, processor, clock, communication interfaces, I/O devices, memory, and so forth. The associate device  114  may comprise a smartphone, tablet, desktop computer, wearable computer, and so forth. 
     Illustrative Processes 
       FIG.  13    depicts a flow diagram  1300  of a process for generating group data  134  using input from an associate  112 , according to some implementations. The process may be implemented at least in part by the user device  110 , associate device  114 , the server  1104 , and so forth. 
     At  1302 , sensor data  1230  is accessed. For example, the sensor data  1230  may comprise lane data  124  indicative of input of entry credential data  122  at a particular lane  104  at a first time as well as image data  128  associated with the particular lane  104  at the first time. 
     At  1304 , the facility management system  118  causes display in a user interface  116  of first image data  128 ( 1 ) obtained at a first time that depicts a first user  102 ( 1 ) and a second user  102 ( 2 ) at a facility  1002 . For example, the system may generate HTML that when rendered by the associate device  114  displays the gallery images  320 . 
     The system may also cause a display of the other elements described above with regard to  FIGS.  3  through  9   . For example, the presentation data  130  may cause display of designator indicia  312 , identifier indicia  314 , and so forth. 
     At  1306 , the system causes display of one or more interface elements  322  in the user interface  116 . Continuing the example above, the HTML may include interface elements such as buttons. 
     At  1308 , input is received from the one or more interface elements  322 . For example, the associate  112  may press one or more of the interface elements  322  to select or deselect particular identifier indicia  314  as belonging to the group. Information indicative of the selection may be sent as associate input data  132  to the facility management system  118 . The associate input data  132  is thus indicative of an association between the first user  102 ( 1 ) and the second user  102 ( 2 ). 
     In some implementations, the display of the user interface  116  may be modified subsequent to the receipt of the associate input data  132 . For example, after designating a previously untracked user  316 , designator indicia  312  may appear in the user interface  116 . 
     At  1310 , group data  134  is generated using the associate input data  132  that is indicative of the association between the first user  102 ( 1 ) and the second user  102 ( 2 ). 
     At  1312 , the first user  102 ( 1 ) and the second user  102 ( 2 ) may be associated with a single identifier. For example, given that the first user  102 ( 1 ) and the second user  102 ( 2 ) are members of the same group, they may be associated with a common billing account number. 
       FIG.  14    depicts a flow diagram  1400  of a process for identifying a user  102  of the facility  1002 , according to some implementations. The process may be implemented at least in part by the user device  110 , associate device  114 , the server  1104 , and so forth. 
     At  1402 , the entry credential data  122  is sent to the user device  110 . For example, the entry credential data  122  may be sent responsive to a request for entry credential data  122 . The entry credential data  122  may be valid for a particular facility  1002 , for a particular period of time, and so forth. In other implementations, the user device  110  may generate entry credential data  122 . 
     At  1404 , sensor data  1230  is received from one or more sensors  108  corresponding to an entry lane  204  of the facility  1002 . For example, the user device  110  may be scanned by the barcode sensor  108 ( 1 ) at the gate  106  to obtain the entry credential data  122 . In another example, the user device  110  may transmit a radio frequency, acoustic, or other signal that conveys the entry credential data  122  to a receiver of the entry lane  204 . A computing device affiliated within the gate  106  may send lane data  124 . The lane data  124  may include information indicative of the particular gate  106 , output from the barcode sensor  108 ( 1 ), data from other sensors  108  associated with the gate  106  such as infrared (IR) photodetectors, and so forth. For example, the lane data  124  may provide information generated by the gate  106  that is indicative of a number of users  102  who have passed through the gate  106 , data indicative of a tailgating violation in which two or more users  102  enter after a single scan of entry credential data  122 , and so forth. 
     At  1406 , the user account associated with the received entry credential data  122  is determined. The entry credential data  122  may be associated with a user account. In one implementation, the entry credential data  122  comprises a temporary token storing a value that may be used to refer to a particular user account record within the facility management system  118 . In other implementations, the entry credential data  122  may comprise encrypted data. 
     At  1408 , first image data  128 ( 1 ) of a user  102  at a first location proximate to the entry lane  204  at the first time is acquired. For example, the image sensors  108 ( 2 ) may be used to acquire image data  128  of the gate  106  located in the lane  104 . 
     At  1410 , tracking of the user  102  within the facility  1002  is initiated, based at least in part on the first image data  128 ( 1 ). For example, the image of the user  102  in the first image data  128 ( 1 ) may be tracked through the entry area  202  and on into the facility  1002 . As the user  102  moves within the facility  1002 , they are tracked using at least the image sensors  108 ( 2 ). For example, second image data  128 ( 2 ) obtained from other image sensors  108 ( 2 ) within the facility  1002  may be obtained. The analysis module  126  may determine a location of the user  102  within the facility  1002  using the second image data  128 ( 2 ). Based on the apparent position of the user  102  within image data  128 , and given the known position of those image sensors  108 ( 2 ) indicated by the physical layout data  1228 , tracking data  1232  indicative of the location and associated with the identifier of the user  102  may be generated. 
     At  1412 , the identity of the user  102  is determined based on the user account. For example, the user account associated with a temporary token may be determined. The identity of the user  102  may comprise information indicative of the user account. 
     At  1414 , a notification may be sent to the user device  110  that is indicative of entry to the facility  1002 . For example, the notification data may be generated and then sent to the user device  110 . In some implementations, the user  102  may use the user device  110  to transmit a confirmation back to the facility management system  118 . Responsive to this confirmation, the facility management system  118  may approve the user account for transactions at the facility  1002 . 
     In some implementations, the identity of the user  102  within the facility  1002  may become uncertain. For example, the user  102  may pass through a crowd of other users  102 , may add or remove a hat or other article of clothing, and so forth. The analysis module  126  may determine that the identity of the user  102  is unreliable at a second time. For example, a confidence value of the identity may be below a threshold at the second time. 
     As described above with regard to  FIG.  3   , the user interface  116  may be presented to the associate  112  to acquire associate input data  132 . This associate input data  132  may then be used to determine the identity of the user  102  with a confidence greater than that previously available. 
     Second image data  128 ( 2 ) of the user  102  at a second location at the second time may be acquired. For example, the image data  128  acquired by the image sensors  108 ( 2 ) up to the time and at the location where identification was lost may be accessed. 
     A first set of user accounts associated with users  102  in the facility  1002  at the second time may be determined. For example, the first set of user accounts may comprise those users  102  which are determined to be still within the facility  1002 . 
     A subset of the first set of user accounts is determined. This subset comprises those users  102  which are not being tracked as of the second time. For example, the subset indicates those users  102  who are untracked. 
     Third image data is determined that comprises previously acquired images of those users  102  indicated by the subset. For example, the image gallery data  212  for those users  102  may be determined. 
     The user interface  116  may then be used to present the image gallery data  212  and the image data  128  contemporaneous with the loss of identification. For example, the user interface  116  may include display of the second image data that depicts the user  102  at the second location at the second time, the third image data that depicts the users  102  that are currently not tracked as of the second time, and one or more interface elements  322 . 
     Associate input data  132  may be accepted using the interface elements  322  of the user interface  116 . This input is indicative of an association between the second image data and the third image data. For example, association may be that the image of the user  102  identified matches a particular one of the gallery images  320 . 
     The identity of the user  102  may then be determined based on the associate input data  132 . If input indicates that the gallery image  320  of user  102  “A” matches the image of the untracked user  316 , the untracked user  316  may be deemed to be user  102  “A”. 
       FIG.  15    depicts a flow diagram  1500  of another process for identifying a user  102  of the facility  1002 , according to some implementations. The process may be implemented at least in part by the user device  110 , associate device  114 , the server  1104 , and so forth. 
     At  1502 , a request for entry credential data  122  is received from a user device  110 . For example, the user device  110  may login to an authentication server and generate the request for entry credential data  122 . 
     At  1504 , the entry credential data  122  is generated. For example, the entry credential data  122  may be generated with an expiration date and time. 
     At  1506 , the entry credential data  122  is sent to the user device  110 . The user device  110  may receive the entry credential data  122 . 
     At  1508 , first lane data  124 ( 1 ) indicative of receipt of the entry credential data  122  at a first lane  104 ( 1 ) of a facility  1002  at a first time is received. For example, the display of the user device  110  may present a machine readable code that is based at least in part on the entry credential data  122 . For example, the machine readable code may comprise a one or two dimensional barcode. 
     At  1510 , first image data  128 ( 1 ) of the first lane  104 ( 1 ) is obtained within a threshold period of the first time is accessed. 
     At  1512 , presence of a user  102  depicted in the first image data  128 ( 1 ) is determined. For example, one or more of a computer vision algorithm or manual input may be used to recognize human faces. 
     At  1514 , the first lane data  124 ( 1 ) is associated with the user  102  depicted in the first image data  128 ( 1 ). For example, the association may be based on the lane data  124  indicating a particular gate  106  and timestamp of entry and determining the first image data  128 ( 1 ) that was obtained with the same gate  106  at the time indicated by the timestamp. 
     At  1516 , an identifier associated with the entry credential data  122  is determined. For example, the identifier may be encoded or encrypted within the entry credential data  122  which is provided as part of the lane data  124 . In another example, the entry credential data  122  may be used to retrieve the identifier. The identifier may comprise a user identifier, account name, account number, login, and so forth. 
     At  1518 , the identifier is associated with the user  102  depicted in the first image data  128 ( 1 ). For example, the analysis module  126  may generate subsequent tracking data  1232  for the user  102  that is indicative of the identifier. 
     In some implementations, some of the operations described above may be performed asynchronously or at a later time. For example, the operations of blocks  1516  and  1518  may occur several seconds or minutes after the preceding operations. For example, during a peak time there may be a temporary backlog of information to be processed by the associate  112 . However, once the associate input data  132  has been received and identification has been made, this identification may be retroactively applied to the observed interactions of the user  102  within the facility  1002 . 
       FIG.  16    depicts a flow diagram  1600  of a process for using an associate to restore tracking of a user  102  in an automated system after a loss, according to some implementations. The process may be implemented at least in part by the user device  110 , associate device  114 , the server  1104 , and so forth. 
     At  1602 , an untracked user  316  is determined to be present within the facility  1002  at a first time. In one implementation, the analysis module  126  may determine that the tracking of a user  102  is unreliable. For example, the tracking data may have a confidence value that has dropped below a threshold value. For example, the computer vision algorithm may be unable to differentiate different users  102  in a crowd. 
     At  1604 , a last known location within the facility  1002  associated with the untracked user  316  is determined. For example, the tracking data  1232  may be processed to determine which identified users  102  are present up to the point of a loss in tracking. 
     At  1606 , a first set of sensor data  1230  acquired before the first time and at the last known location is accessed. 
     At  1608 , a set of currently untracked users  316  is determined. For example, the set of currently untracked users  316  may comprise those users  102  for which recent tracking data  1232  is unavailable. 
     At  1610 , a second set of sensor data  1230  that is acquired at the time of entry to the facility  1002  and which is associated with the set of untracked users  316  is accessed. For example, this may comprise the image gallery data  212  for the users  102  who are currently untracked. 
     At  1612 , at least a portion of the first set of sensor data and at least a portion of the second set of sensor data is sent to an associate device  114 . For example, presentation data  130  may be generated that references at least a portion of the image gallery data  212  and the image data  128 . 
     At  1614 , the facility management system  118  receives the associate input data  132  that associates appearance of the user  102  in the first set of sensor data-with appearance of the same user  102  in the second set of sensor data. For example, the associate input data  132  may designate a bounding box around the image of a previously untracked user  316 . Based on a comparison with the image gallery data  212 , the associate  112  may also provide information indicative of the identity of the untracked user  316 . 
       FIG.  17    depicts a flow diagram  1700  of a process for using an associate  112  to identify a user  102  that is unidentified by an automated system, according to some implementations. The process may be implemented at least in part by the user device  110 , associate device  114 , the server  1104 , and so forth. 
     At  1702 , first image data  128 ( 1 ) obtained within the facility  1002  is accessed. 
     At  1704 , presence of an unidentified user  102  is determined at a first time. For example, a confidence value of an identifier associated with the user  102  depicted in the first image data  128  may drop below a threshold value. 
     At  1706 , image gallery data  212  is determined that comprises at least a portion of previously acquired image data  128  associated with unidentified users. For example, the images of unidentified users  102  obtained at the entry area  202  may be retrieved and presented in the image gallery data  212 . 
     At  1708 , the image gallery data  212  and at least a portion of the first image data  128 ( 1 ) are sent to the associate device  114 . 
     At  1710 , associate input data  132  is received from the associate device  114 . The associate input data  132  may comprise data that designates a user  102  depicted in the first image data  128 ( 1 ) is the same as one of the one or more users  102  depicted in the image gallery data  212 . 
     At  1712 , the unidentified user  102  is associated with a particular identifier, based on the associate input data  132 . For example, the designated user  102  indicated by the associate input data  132  may be associated with the unidentified user  102 . 
     The processes discussed herein may be implemented in hardware, software, or a combination thereof. In the context of software, the described operations represent computer-executable instructions stored on one or more non-transitory computer-readable storage media that, when executed by one or more processors, perform the recited operations. Generally, computer-executable instructions include routines, programs, objects, components, data structures, and the like that perform particular functions or implement particular abstract data types. Those having ordinary skill in the art will readily recognize that certain steps or operations illustrated in the figures above may be eliminated, combined, or performed in an alternate order. Any steps or operations may be performed serially or in parallel. Furthermore, the order in which the operations are described is not intended to be construed as a limitation. 
     Embodiments may be provided as a software program or computer program product including a non-transitory computer-readable storage medium having stored thereon instructions (in compressed or uncompressed form) that may be used to program a computer (or other electronic device) to perform processes or methods described herein. The computer-readable storage medium may be one or more of an electronic storage medium, a magnetic storage medium, an optical storage medium, a quantum storage medium, and so forth. For example, the computer-readable storage media may include, but is not limited to, hard drives, floppy diskettes, optical disks, read-only memories (ROMs), random access memories (RAMS), erasable programmable ROMs (EPROMs), electrically erasable programmable ROMs (EEPROMs), flash memory, magnetic or optical cards, solid-state memory devices, or other types of physical media suitable for storing electronic instructions. Further, embodiments may also be provided as a computer program product including a transitory machine-readable signal (in compressed or uncompressed form). Examples of transitory machine-readable signals, whether modulated using a carrier or unmodulated, include, but are not limited to, signals that a computer system or machine hosting or running a computer program can be configured to access, including signals transferred by one or more networks. For example, the transitory machine-readable signal may comprise transmission of software by the Internet. 
     Separate instances of these programs can be executed on or distributed across any number of separate computer systems. Thus, although certain steps have been described as being performed by certain devices, software programs, processes, or entities, this need not be the case, and a variety of alternative implementations will be understood by those having ordinary skill in the art. 
     Additionally, those having ordinary skill in the art will readily recognize that the techniques described above can be utilized in a variety of devices, environments, and situations. Although the subject matter has been described in language specific to structural features or methodological acts, it is to be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or acts described. Rather, the specific features and acts are disclosed as illustrative forms of implementing the claims.