Patent Publication Number: US-11656749-B2

Title: Machine learning in video classification with schedule highlighting

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a continuation of U.S. application Ser. No. 16/916,121, filed Jun. 30, 2020, now U.S. Pat. No. 11,354,024, which is a continuation of U.S. application Ser. No. 15/905,706, filed Feb. 26, 2018, now U.S. Pat. No. 10,754,514, which claims priority under 35 U.S.C. § 119(e) to U.S. Provisional Patent Application No. 62/465,788, “System and Method for Video Content Searching,” filed Mar. 1, 2017, and to U.S. Provisional Patent Application No. 62/465,790, “System and Method and Interface for Video Content Searching,” filed Mar. 1, 2017, all of which are incorporated herein by reference in their entirety. 
    
    
     BACKGROUND 
     1. Field of the Disclosure 
     This disclosure pertains in general to media content classification, and more specifically to classifying portions of media content using machine-learning detectors and modifying user interface elements based on the classification. 
     2. Description of the Related Art 
     As the creation and sharing of digital media becomes more widespread, it becomes increasingly difficult to process the flood of information to find desired content. For example, the number of video files that are created and shared on the Internet have exceeded what can be manually reviewed by one or even a team of curators. However, conventional search engines are limited in their ability to search video content. Text-based search engines search for content using search strings that match text descriptors associated with media content. Often, text cannot accurately describe video content, and the search engine is unable to identify objects within the video based on text inputs. 
     SUMMARY 
     Described herein are systems and methods that search for objects, faces, or other items selected by users in media content items to find media content items (such as videos or frames of video) where the media content preferred by users appear. The media content items can be live or pre-recorded. The systems employ detectors to identify objects within media content items. The detectors configured to detect an object can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. A detector can detect a predetermined set of visual features representing objects. For example, a detector can detect one or more entities (e.g., an object, a particular individual, a human, etc.), an entity of a particular characteristic (e.g., a fawn pug puppy, an Asian female wearing a blue jacket, etc.), an action (e.g., flying, sailing, etc.), a color, a texture, a shape, a pattern, and the like. 
     The systems provide user interfaces. The user interfaces are configured to allow users to review results of a search in media content items for a selected object, pinpoint relevant portions of media content items where the selected object is determined to be present, review and retrain detectors, specify example media content items for retraining detectors, providing search result feedback, reviewing video monitoring results and analytics, and the like. 
     The features and advantages described in the specification are not all inclusive and, in particular, many additional features and advantages will be apparent to one of ordinary skill in the art in view of the drawings and specification. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the inventive subject matter. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The teachings of the present disclosure can be readily understood by considering the following detailed description in conjunction with the accompanying drawings. 
         FIG.  1    is a block diagram of an overall system environment illustrating a media detection system providing media detection services, according to an embodiment. 
         FIGS.  2 A through  2 C  are example user interfaces for presenting search results, according to one embodiment. 
         FIGS.  3 A through  3 B  illustrate example user interfaces for users to select detectors, according to various embodiments. 
         FIGS.  4 A through  4 D  illustrate an example user interface for users to configure detectors, according to one embodiment. 
         FIGS.  5 A through  5 D  illustrate a user interface for highlighting searched content, according to one embodiment. 
         FIGS.  6 A through  6 E  illustrate example user interfaces for presenting analytics of a video stream, according to one or more embodiments. 
         FIG.  7    is a flow chart of an example process of playing back a video, according to one embodiment. 
         FIG.  8    is a flow chart of an example process of updating a detector, according to one embodiment. 
         FIG.  9    is a flow chart of an example process of playing back a video, according to one embodiment. 
         FIG.  10    is a flow chart of an example process of monitoring a video, according to one embodiment. 
         FIG.  11    is a high-level block diagram of a computer for implementing different entities illustrated in  FIG.  1   . 
     
    
    
     The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee. 
     DETAILED DESCRIPTION 
     The Figures (FIG.) and the following description relate to various embodiments by way of illustration only. It should be noted that from the following discussion, alternative embodiments of the structures and methods disclosed herein will be readily recognized as viable alternatives that may be employed without departing from the principles discussed herein. Reference will now be made in detail to several embodiments, examples of which are illustrated in the accompanying figures. It is noted that wherever practicable similar or like reference numbers may be used in the figures and may indicate similar or like functionality. 
     System Overview 
       FIG.  1    is a block diagram of an overall system environment illustrating a media detection system  140  providing media detection services, according to an embodiment. The media detection system  140  searches for media content preferred by users (referred to herein as “preferred content” or “selected object”) in media content items to find media content items (such as videos or frames of video) where the media content preferred by users appear. The media detection system  140  provides user interfaces that allow users to pinpoint relevant segments where media content preferred by the users appear, that allow users to configure detectors to search for content, that highlight content preferred by users in media content items, and that present monitoring results and analytics of the results. As shown in  FIG.  1   , the overall system environment includes the media detection system  140 , one or more user devices  110 , one or more content systems  180 , and a network  130 . Other embodiments may use more or fewer or different systems than those illustrated in  FIG.  1   . Functions of various modules and systems described herein can be implemented by other modules and/or systems than those described herein. 
     A user device  110  (also referred to herein as a “client device”) is a computing system used by users to interact with the media detection system  140 . A user interacts with the media detection system  140  using a user device  110  that executes client software, e.g., a web browser or a client application  120 , to connect to the media detection system  140  (via the system interface module  142 ). The user device  110  displayed in these embodiments can include, for example, a mobile device (e.g., a laptop, a smart phone, or a tablet with operating systems such as Android or Apple IOS etc.), a desktop, a smart automobiles or other vehicles, wearable devices, a smart TV, and other network-capable devices. 
     The user device  110  can present media content provided by the media detection system  140  or a content systems  180 . In some embodiments, the user device  110  includes an embedded video player such as, for example, the FLASH player from Adobe Systems, Inc., or any other player adapted for various media formats used in the media detection system  140 . 
     A content system  180  is a computing system that generates and/or hosts media content. For example, the content system provides a media content hosting service that users can upload, browse, search for, stream, and/or play media content items. As another example, the content system  180  is a network video camera that captures images of its surrounding area and streams the captured content. The content system  180  may include a content store  182  that stores media content items. 
     The network  130  facilitates communication between the user devices  110  and the media detection system  140 . The network  130  is typically the Internet, but may be any network, including but not limited to a LAN, a MAN, a WAN, a mobile wired or wireless network, a cloud computing network, a private network, or a virtual private network. 
     The media detection system  140  includes a system interface module  142 , a preferred content definition module  144 , a target content definition module  146 , a search engine  148 , a user interface module  150 , a detector management module  152 , an analytics module  154 , a search store  156 , a detector store  158 , a media content store  160 , and an analytics store  162 , all of which are further descried below. Other conventional features of the media detection system  140 , such as firewalls, load balancers, authentication servers, application servers, failover servers, and site management tools are not shown so as to more clearly illustrate the features of the media detection system  140 . The illustrated components of the media detection system  140  can be implemented as single or multiple components of software or hardware. In general, functions described in one embodiment as being performed by one component can also be performed by other components in other embodiments, or by a combination of components. Furthermore, functions described in one embodiment as being performed by components of the media detection system  140  can also be performed by one or more user devices  110  in other embodiments if appropriate. 
     The system interface module  142  coordinates communication between the user devices  110 , the content systems  180 , and the media detection system  140 . For example, the system interface module  142  receives requests from the user devices  110  and interfaces with one or more other modules of the media detection system  140  to process the requests. The system interface module  142  also receives media content items from the user devices  110  and/or the content systems  180 . The system interface module  142  transmits media content items and/or user interfaces to the user devices  110 . As described herein, a media content item is a file (i.e., a collection of data) including media content such as pictures, videos, movie clips, games, sound tracks, and the like. The file can be various file formats. Although videos are used as examples to illustrate operations of the media detection system  140 , this is done for the purpose of simplicity, and is not intended to be limiting in any way. 
     The system interface module  142  may process media content received from the user devices  110  and/or from the content systems  180 . For example, the system interface module  142  assigns a unique media content item identifier to a media content item. The media content item can be identified by the unique media content item identifier. Other processing operations include, for example, formatting (e.g., transcoding), compression, metadata tagging, content analysis, classification/detection, and other data processing. The system interface module  142  may store a media content item in the media content store  154 . The media content store  154  is a storage system where media content items are stored. A media content may be associated with metadata such as a location (e.g., URL (Uniform Resource Locator)), a title, a descriptor, and the like. As further described below, the one or more media content items received from the user devices  110  may be used to define a preferred content for which the media detection system  140  searches. The received media content items may also be used to create detectors which the media detection system  140  employs to search for preferred media content. In addition, the media detection system  140  may search in the received media content items for preferred media content. 
     The system interface module  142  interfaces with the content system  180  to process one or more media content items. For example, a user specifies a set of media content items for the media detection system  140  to process. The user provides locations such as URLs to the media content items in which the media detection system  140  searches for preferred media content. In some embodiments, the system interface module  142  obtains the one or more media content items from the content systems  180  and processes the obtained media content items locally. In some embodiments, the system interface module  142  interfaces with the content systems  180  such that the media detection system  140  can search for preferred media content in the media content items hosted by the content systems  180 . 
     The preferred content definition module  144  defines preferred content for which the search engine  146  searches. Preferred content can be a set of visual features describing items such as objects, ideas, or concepts. The visual features can be static or dynamic over time. In various embodiments, the preferred content definition module  144  defines preferred content according to a user&#39;s specification. The user&#39;s specification can include a set of media content items. The set of media content items (or media content items representing the set of detectors) include visual features exemplifying the user&#39;s preferences for the preferred content. The user may upload the set of media content items to the media detection system  140 . Alternatively, the user may browse media content items stored in the media detection system  140  and select from among the browsed media content items. For example, the user browses media content items used to train detectors. The user can upload and/or select the set of media content items via one or more user interfaces provided by the user interface module  150 . Via the one or more user interfaces, the user can also identify portions of media content items such as a video segment, a section of a video frame, or a section of an image that include the visual features. For example, via a user interface, the user identifies a video frame that includes content representing “Saylor Twift wearing a red dress and sunglasses smiling”, which is the preferred content. 
     The preferred content definition module  144  may associate text descriptors with defined preferred content. A text descriptor describes characteristics of the preferred content. The preferred content definition module  144  may store the preferred content in a search store  154 . Text descriptors associated with the preferred content are also stored in the search store  154 . The text descriptors can be used to identify searches. 
     The target content definition module  146  defines target content in which the search engine  146  searches for preferred content. Target content can include one or more target media content items such as videos. The videos can be pre-recorded or can be live videos. The user can provide the one or more target media content items in a variety of ways. For example, the user provides the web location of the one or more target media content items to the media detection system  140 . As another example, the user browses the content system  180  via the media detection system  140  and selects the one or more target media content items. As a further example, the user searches for the one or more target media content items in the content system  180  directly or via the media detection system  140 . As yet another further example, the user uploads the one or more target media content items to the media detection system  140 , or browses and selects the target media content items from media content items stored in the media detection system  140 . The user can provide the one or more target media content items via one or more user interfaces provided by the user interface module  150 . For example, via a user interface, the user interfaces with a native search interface of a content system  180  and searches for target videos by typing in key words “Saylor Twift red dress” in the native search interface. 
     The search engine  148  searches for preferred content in one or more target content items. In various embodiments, the search engine  148  employs one or more detectors to search for the preferred content in a target content item. The one or more detectors determine whether the preferred content is present in the target content item. A detector is configured to detect one or more items, such as a selected object, a face, an identified person, a feature of an item, and the like, within frames of video. A detector can be a classifier configured to classify a frame of video based on a likelihood that the frame of video includes a particular item within the frame. The detector can output a Boolean result of the classification (e.g., “true” if the frame includes the item or “false” if not), or can output a confidence score representative of the likelihood that the frame includes the item (as described below). In some embodiments, a detector can detect multiple items within the frame, and in some embodiments, multiple detectors can detect a single item with the frame. The search engine  148  can select the one or more detectors based on the preferred content. For example, the search engine selects the one or more detectors from detectors stored in the detector stores  158 , that are associated with the media content items used to define the preferred content. 
     For each target content item, the search engine  148  outputs one or more confidence scores. A confidence score indicates a likelihood of the preferred content being present in the media content item (or a portion thereof). The search engine  148  may further output one or more locations (e.g., a set of pixels) of the preferred content being present in a target media content item (or a portion thereof). If the preferred content appears multiple times in a media content item, the search engine  148  may determine an overall confidence score indicating the preferred content being present in the media content item using the confidence scores. The search engine  148  associates the one or more confidence scores and the one or more locations with the target content item and stores the one or more confidence scores and the one or more locations associated with the target content item in the search store  154 . For a particular item detected to be present within a particular video frame, the confidence score associated with the item may be an average of confidence scores outputted by multiple detectors, if multiple detectors are used. 
     A detector configured to identify an object within media content items can be trained using a machine learned model (e.g., a convolutional neural network) as applied to a set of example media content items that include the object. The search engine  148  can select a set of detectors stored in the detector store  156  to conduct the search. A detector can detect a predetermined set of visual features representing items. For example, a detector can detect one or more entities (e.g., an object, a particular individual, a human, etc.), an entity of a particular characteristic (e.g., a fawn pug puppy, an Asian female wearing blue jacket, etc.), an action (e.g., flying, sailing, etc.), a color, a texture, a shape, a pattern, and the like. 
     The user interface module generates user interfaces. The user interfaces are configured to allow users to review search results, pinpoint relevant portions of media content items where the preferred content is determined to be present, review detectors, configure detectors, specify example media content items for configuring detectors, providing feedback on search results while reviewing the search results, reviewing monitor results, and/or review analytics of monitor results. 
     In some embodiments, the user interface module  150  generates user interfaces that allow users to pinpoint relevant portions of media content items that are determined to include the preferred content. For example, if the search engine  148  determines that a video includes the preferred content, the user interface module  150  generates a user interface that allows a user to review the video. The user interface module  150  may generate a user interface presenting a list of video content items that are determined to include the preferred content. A user can select a video from the list of videos to review. Based on the user&#39;s selection, the user interface module  150  plays the selected video. The user interface includes a video player that plays the video. The user interface may include a progress bar indicating a progress of playing the video. The user interface module  150  may generate user interface elements (e.g., bars) overlaid on top of the progress bar to illustrate video segments where the preferred content determined to be present. If a confidence value for a particular video frame is greater than the threshold confidence value, the preferred content is determined to be present in the video frame. 
     The user interface elements are visually distinguished from the progress bar. A starting location of a user interface element is determined based on a starting time point of the video segment. A length of the user interface element is determined according to a duration of the video segment. The user interface module  150  can obtain the confidence scores from the search store  156 . The starting time point of the video segment can be determined according to a timestamp (absolute or relative to the beginning of the video) of a beginning video frame of the video segment. The duration can be determined in a similar manner. In some embodiments, the user interface module  150  generates a user interface element if the corresponding video segment lasts at least a threshold duration. The user interface module  150  configures the user interface such that a user can input a threshold confidence value. A user can input the threshold confidence value concurrently when the video is being played. The user interface module  150  dynamically configures the user interface elements for illustrating the relevant video segments according to the user&#39;s input of the threshold confidence value. 
     In some embodiments, the user interface module  150  generates user interfaces that allow users to configure detectors. In particular, the user interface module  150  generates user interfaces that allow users to configure example media content items (e.g., images, videos, portions of images, portions of videos such as video segments, portions of video frames) for training and/or updating detectors. The user interface module  150  generates user interface elements configured to allow users to provide example media content items from various source locations. Via a user interface element, a user can configure to upload media content items stored locally on the user device  110  to the media detection system  140 . Via another user interface element, a user can configure to use videos provided (e.g., hosted or generated) by the content system  180 . Via a further user interface element, a user can configure to use a portion of a media content item. An example media content item can be a positive example or a negative example. Positive example media content items include visual features that a detector is configured to search for in preferred content. Negative example media content items include visual features that a detector is configured to avoid in preferred content. 
     The user interface element module  150  generates a user interface that allows users to provide feedback for updating detectors while reviewing search results. For example, the user interface element module  150  includes user interface elements via which a user can confirm whether a video frame which is determined to include preferred content. In other words, the user interface elements are configured to receive user input on whether a detector&#39;s output is correct. If the user confirms that the video frame includes the preferred content, the particular video frame (or portions thereof) is included as a positive example in the example media content items for updating the detector. Conversely, if the user rejects that the video frame includes the preferred content, the particular video frame (or portions thereof) is included as a negative example in the example media content items for updating the detector. The detector can be updated concurrently when it is being employed by the search engine  148 . 
     The user interface element module  150  generates user interfaces that highlight sections of images or video frames that are determined to include the preferred content. For example, if the search engine  148  determines that a video includes the preferred content, the user interface module  150  generates a user interface that allows a user to review the video. The user interface includes a video player that plays the video. The user interface element module  150  further generates user interface elements (e.g., a border box) configured to surround the portion of the video frame where the preferred content is determined as being present. The user interface elements are overlaid on top of the region displaying the video. The location and dimension of the user interface elements can be determined according to the search engine&#39;s output. The user interface elements track the preferred content over time. To improve user experience, the user interface element module  150  may interpolate locations of the user interface elements across consecutive video frames to avoid abrupt location changes. 
     The user interface element module  150  generates user interfaces that present video monitoring results. The media detection system  140  can monitor live video streams for preferred content. For example, the user interface element module  150  generates a user interface that includes user interface elements illustrating how many times the preferred content is detected during a time period on top of a calendar view. As such, a user can visualize detection events via the user&#39;s calendar. The user can select to review a particular detection event such as a time stamp of the video frame, the particular video frame where the preferred content is determined to appear, and the like. A user can request to review analytics of the monitoring results such as an accumulated count of occurrences of the preferred content over a time interval, a total count of occurrences of the preferred content, and/or an average count of occurrences of the preferred content over a time interval. The user interface element module  150  generates user interfaces that include different user interface elements for presenting the analytics. 
     The detector management module  152  trains and manages detectors. A detector can be configured to search for a particular set of media content features in target media content items. In various embodiments, the detector management module  152  creates the detectors by training one or more machine learning models using training data. The training data include example media content items provided by a user. The example media content items can be obtained from a variety of sources. For example, a user specifies media content items by selecting media content items stored in the media content store  158 , uploading media content items to the media detection system  140 , selecting portions of a media content item, providing locations of media content items to the media detection system  140 , and the like. The training data can include positive examples and/or negative examples. A positive example includes desired features and the negative example includes undesired characteristics. For example, a user specifies positive examples to the media detection system  140  to indicate that media content being visually similar to the positive example is desired. The negative example is used to indicate undesired content. 
     The detector management module  152  may generate a label describing a detector. In particular, the label describes characteristics of visual features the detector is configured to search for. A user can provide the label to the media detection system  140 . The detector management module  152  associates the label with the detector and stores the detector associated with the label in the detector store  156 . 
     The detector management module  152  may update detectors using user feedback. For example, if a user confirms (or disapproves) a detector&#39;s output, the detector management module  152  includes the media content item as a positive example (or a negative example) in example media content items used for training the detector. The update may be performed concurrently when the detector is being employed. 
     The detector management module  152  may determine popularity of detectors stored in the detector store  158 . The detector management module  152  tracks a number of times the detector employed by the search engine  148  over a time period. The detector management module  152  may determine a popularity score based on the number of times. The detector management module  152  associates the popularity score (or the number of times) with the detector and stores the association in the detector store  158 . 
     The analytics module  154  analyzes search results. For example, the analytics module  154  obtains search results from the search store, and determines an accumulated count of preferred content being present in a time interval, a total count of preferred content being present, an average count of preferred content being present in a time interval, and the like. The accumulated count of preferred content being present in a time interval is determined by summing up a number of times that the preferred content is determined to be present in video frames in a time interval (e.g., one hour, one day, one month). The video frames are associated with time stamps in the time interval. The total count of preferred content being present is determined by summing up a number of times that the preferred content is determined to be present in video frames since a predetermined time point (e.g., a beginning of the video). The video frames are associated with time stamps in the time interval. The average count of preferred content being present in a time interval is determined by summing up a number of times that the preferred content being present in the same period (e.g., between 9 AM and 10 AM) over multiple time durations (e.g., 5 days) and dividing the number of times by the number of multiple time durations. 
     Example User Interface for Presenting Search Results 
       FIGS.  2 A through  2 C  are example user interfaces for presenting search results, according to one embodiment. The example user interface  200  includes a video player that presents videos. In other embodiments, the arrangements of elements in the user interface may be different. 
     The media detection system  140  provides the user interface (UI)  200  to a user device  100  for presenting videos as search results. Referring now to  FIG.  2 A , the user interface  200  includes user interface elements  204  through  209 . The user interface elements  204  through  209  allow a user to review videos determined by the media detection system  140  to include the preferred content. Specifically, the user can pinpoint relevant sections of the videos that are determined to include the preferred content. The user can also configure the preferred content, and configure the relevancy of the videos. 
       FIG.  2 A  and the other figures use like reference numerals to identify like elements. A letter after a reference numeral, such as “ 209   a ,” indicates that the text refers specifically to the element having that particular reference numeral. A reference numeral in the text without a following letter, such as “ 209 ,” refers to any or all of the elements in the figures bearing that reference numeral (e.g. “ 209 ” in the text refers to one or more of the reference numerals “ 209   a ” and/or “ 209   f ” in the figures). 
     The user interface  200  includes a display area  201  for displaying a video  202  that is determined to include preferred content. The user interface element  204  visualizes the progress of the video  202  being played. The user interface element  240  uses visually distinguished elements to illustrate the progression. For example, the user interface element  240  is a progress bar, a segment of the bar is of a first color to indicate an amount of the video  202  that has been played and the remaining segment of the bar is of a different color to indicate the remaining amount of the video  202  to be played. The segments can also be of different patterns, brightness, thickness, and the like so long as they are visually distinguished. 
     The user interface  200  also includes a user interface element  208  configured to control playback of the video  202 . In the illustrated example, the user interface element  208  is a seek button overlaid on top of the user interface element  204 . The user interface element  208  is configured to be moved along the user interface element  204  to select a particular temporal location in the video  204  to be played. Video frames after the selected temporal location in the video  204  are to be presented. 
     The user interface  200  further includes user interface elements  209  visualizing temporal portions of the video  202  that includes preferred content. The user interface element  209  can be a bar overlaid on top the user interface element  204 . When being overlaid on top of the user interface element  204 , the user interface element  209  is positioned at a location of the user interface element  204  that corresponds to the temporal portion of the video  202 . The length of the user interface element  209  is proportional to an interval of the video  202  that includes the preferred content. As one example, assuming that the video  202  is 10 minutes long, the user interface element  209   a  indicates that the interval between 73 seconds and 76 seconds include the preferred content. The user interface element  209  is visually distinguished from the user interface element the user interface element  204 . 
     The user interface  200  is configured to include user interface elements  209  if a confidence score associated with a video frame is greater than a threshold confidence score. The confidence score indicates a likelihood of a video frame including preferred content. If the confidence score is greater than a threshold confidence score, the video frame is determined to include preferred content. As described previously, the user interface module  150  obtains the confidence scores associated with the video frames from the search engine  148 . 
     In some embodiments, the user interface module  150  configures a user interface element  209  such that a corresponding time interval of consecutive frames determined to include preferred content is at least a threshold time interval. For example, the user interface module  150  determines a time interval of a set of consecutive video frames associated with confidence scores greater than the threshold confidence score. In some embodiments, an average confidence score of the set of consecutive video frames is determined. The average confidence score is greater than the threshold confidence score. It is possible that a video frame included in the set of consecutive video frames is associated with a confidence score that is below the threshold confidence score. The user interface module  150  compares the time interval to the threshold time interval to determine whether to generate a user interface element  209 . If the time interval is less than the threshold time interval (e.g., 0.5 s), the user interface module  150  does not generate a user interface element  209 . The threshold time interval may a system default value configured by a system administrator of the media detection system  140  or configured by the user. By doing this, the user interface module  150  prevents the user interface  200  from being overcrowded by user interface elements  209  to reduce visual distractions thereby improving user experiences. Users are directed to video segment including more substantial relevant content. False positive search results are also reduced because the user interface module  150  accounts for the analysis of a series of consecutive frames. A false positive result is a video frame that does not include preferred content but is determined to include the preferred content. 
     The user interface  200  includes user interface elements  206  and  207  for users to configure the threshold confidence score. The threshold confidence score is used to determine whether the preferred content appears in a video frame as described above. In the illustrated example, the user interface element  206  is a sliding scale and the user interface element  207  is a slider configured to be moved along the user interface element  206 . Moving the user interface element  207  generates signals representing the user&#39;s input of the threshold confidence score. Other embodiments of the user interface  200  can include a text box where the user types in the threshold confidence value, a drop-down menu where the user can select the threshold confidence value, buttons where the user can click on to adjust the threshold confidence value, and other designs where the user can input a numerical value. The user can configure the threshold confidence score concurrently while the video  202  is being played. 
     The user interface element  205  is configured to receive user inputs specifying which search results to be displayed. In the illustrated example, the user interface element  205  is a drop-down menu displaying the user&#39;s search history of preferred content. According to the user&#39;s selection of “Surfing” which is a text descriptor associated with the preferred content, corresponding search results are displayed. 
     Now turning to  FIG.  2 B , the user interface element  208  is moved. The video frame corresponding to the temporal location of the user interface element  208  is displayed. Because the user interface element  208  overlaps the user interface element  209   c , the displayed frame includes preferred content. As illustrated, the displayed video frame displays a surfer. The user interface  200  further displays a user interface element  210  that presents the confidence score associated with the video frame. 
     As illustrated in  FIG.  2 C , the location of the user interface element  207  is moved closer to the rightmost end of the user interface element  206 , compared to the location of the user interface element  207  illustrated in  FIG.  2 A . This location adjustment increases the threshold confidence score, which may affect the determination of which video frames include the preferred content. Some video frames that are determined to include the preferred content may be associated with confidence scores that are not greater than the adjusted confidence score. The user interface module  150  configures the user interface  200  dynamically. In particular, the user interface module  150  dynamically updates the user interface  200  by updating the user interface elements  209  according to the threshold confidence score input by the user. In the illustrated example, because the threshold confidence score is increased, the user interface elements  209  are more sparse compared to the user interface elements  209  illustrated in  FIG.  2 A , indicating that fewer video frames include the preferred content. 
     Example User Interface for Providing Detectors 
       FIGS.  3 A through  3 B  illustrate example user interfaces for users to select detectors, according to various embodiments. The user interface  300  illustrated in  FIG.  3 A  allows users to browse and to search for detectors stored in the detector store  156 . The user interface  300  includes a user interface element  302  providing categories of detectors. A user can browse detectors based on categories presented via the user interface element  302 . User interface elements  303  correspond to different categories of detectors. If a use interface element  303  is triggered (e.g., clicked on, pressed, toggled, etc.), the user is presented with detector representations of the categories corresponding to the triggered user interface element. A detector representation includes images and/or text descriptors representing preferred content the detector is configured to detect. For example, the user interface element  303   e  “Cars” is activated and the user is presented with detector representations of detectors of the category cars. The user interface element  303  is configured such that it appears visually different when activated and when not activated. As illustrated, the user interface element  303   e  is of a different color (e.g., black) from the user interface elements  303   a  through  d  that are not activated. The user interface element  304  allows a user to browse additional categories. For example, the user interface element  304  is configured such that its activation generates a signal configured to expand the user interface element  302  to present additional detector categories. 
     The user interface  300  includes a user interface element  305  that allows a user to search for detectors. In the illustrated example, the user interface element  305  is a text box configured to receive user input. A user can input texts such as labels describing detectors. For example, pugs, dogs, show dogs, dog running, and the like are example labels. 
     The user interface  300  includes sections  308  and  309  for presenting detection representations representing detectors of a category. Users can browse detector representations presented in the sections  308  and  309 . In the illustrated example, detection representations of popular detectors are displayed in the section  308  and detection representations of all detectors are displayed in the section  308 . Popular detectors are detectors of which the associated popularity score greater than a threshold popularity score. In some embodiments, the user interface module  150  receives rankings of the detectors associated with the detectors stored in the detector store  156  and organizes the detectors according to the rankings. In some embodiments, the user interface module  150  receives popularity of the detectors associated with the detectors stored in the detector store  156  and organizes the detectors according to the popularity. The user interface module  300  provides the detectors according to the order. 
     User interface elements  306  and  310  provide detection representations of individual detectors. For example, the user interface element  306   b  provides a picture of a race car, the user interface element  306   d  provides a picture of a vintage car, the user interface element  310   a  provides a picture of a man holding a gun, and the user interface element  310   b  provides a picture of a sedan. In addition, user interface elements  306  ( 310 ) include text descriptors  307  ( 311 ) describing the detector. For example, the user interface element  306   a  provides the user interface  307   a  providing the text descriptor “Sports Car,” the user interface element  306   c  provides the user interface  307   c  providing the text descriptor “Car Accident Site,” and the user interface element  310   c  provides the user interface  311   c  providing the text descriptor “Sports Car.” In some embodiments, the user interfaces  307  (or  311 ) allow users to modify text descriptor. 
     Now referring to  FIG.  3 B , the user interface  350  presents representations of detectors of the surfing category. For example, a user inputs “surfing” into the user interface element  305  and is directed to the user interface  350 . The user interface  350  provides user interface elements  355  providing images of the detectors. The user interface elements  355  are arranged into a matrix. A user can select a particular detector by clicking on a corresponding user interface element  355 . The user interface elements  352  allow users to browse detectors by pages. 
     Example User Interface for Configuring Detectors 
       FIGS.  4 A and  4 C  illustrate an example user interface for users to configure detectors, according to one embodiment. As described previously, detectors are used to detect content of particular visual features specified by users. Detectors can be used to search for preferred content. A detector is created by a series of media content items used to define the preferred content. As illustrated in  FIG.  4 A , a user interface  400  includes user interface elements  402  through  411  for users to provide input to configure a detector. 
     The user interface element  402  is a text box where a user can input a detector name designating the detector. As illustrated, the user inputs to configure a new detector “Saylor Twift.” 
     The user interface elements  403 - 404  allow users to provide example media content items for configuring the detector “Saylor Twift.” The example media content items for configuring the detector can be selected from the media content items stored on the media detection system  140  and/or uploaded to media detection system  140 . The user interface element  403  is configured to direct the user to select from media content items stored on the media detection system  140 . A user can browse, search for, and select media content items stored on the media detection system  140  by actuating the user interface element  403 . A detector can be represented by a media content item used to create the detector. 
     The user interface element  404  allows users to upload example media content items for creating detectors. As illustrated, when the user interface element  404  is actuated, the user is presented with the options to select the sources where example media content items used for training detectors should be obtained. The user interface elements  408  through  410  allow users to configure specific sources for obtaining example media content items for configuring a detector. Each of the user interface elements  408  through  410  is configured to direct the user to select a particular source where media content items can be obtained. For example, the user interface element  408  is configured to allow a user to select the user device  110  as a source. By actuating the user interface element  408 , a user can be configured to upload example media content items stored on the user device  100  to the media detection system  140  for configuring detectors. As illustrated in  FIG.  4 B , by actuating the user interface element  408 , the user interface  400  is expanded to include a user interface element  420  configured to present example media content items  421  that have been selected by the user. The user interface element  420  is configured to generate a signal to trigger the media detection system  140  (e.g., detector management module  152 ) to obtain media content items of which the representations are positioned in the user interface element  420 . The obtained media content items are stored in the media detection system  140 . As illustrated, the user interface  400  is configured to illustrate a status of the media content items being uploaded. Checkmarks are used to illustrate that the media content items  421  have been uploaded to the media detection system  140 . 
     Referring back to  FIG.  4 A , the user interface element  409  is configured to allow a user to select a content system  180  as a source. A user can specify a web location (e.g., an IP address) of the content system  180  and/or a web location (e.g., an URL) of media content items hosted by the content system  180 . The user interface element  409  is configured to generate a signal to trigger the media detection system  140  to obtain an example media content item by visiting the web location. The user interface  400  may be configured to prompt users to provide user credentials for accessing the content system  180 . Multiple media content items can reside at the same web location, and the media detection system  140  can obtain one or more of the multiple content items that reside at the same web location. If a media content item is a video, the user interface element is configured to allow a user to select one or more video frames of the media content item, to browse the series of video frames, to search for a video frame at a particular time point, to select a geometrical portion of a video frame, and perform other editing actions. 
     The user interface element  410  is configured similar to the user interface element  409  and description is omitted herein. 
     The user interface element  411  is configured to allow a user to edit selected media content items. The edited media content items are used to configure a detector. For example, the user interface element  411  is configured to generate a signal to activate a video editing tool if triggered. Via the video editing tool, a user can select a segment of the video and/or a portion of a video frame for configuring a detector. 
     The user interface element  407  is configured to allow a user to specify whether a provided media content item is a positive example or a negative example. The user interface element  407  is configured to generate a first signal indicating that a media content item is a positive example such that the detector management module  152  creates the detector to search for content having similar features as the media content item. A second signal is generated to indicate that another media content item is a negative example such that the detector management module  152  creates the detector not to search for content having similar features as this media content item. 
     The user interface element  406  is configured to allow a user to provide a set of labels describing a detector. The label may describe the category of the detector, content the detector is configured to search for, and other information of the detector. Labels can be used to facilitate users to search for and distinguish different detectors. The media detection system  140  stores labels associated with detectors. In the illustrated example, the user inputs texts “Celebrity” as a label to be associated with the detector designated by “Saylor Twift.” 
     The user interface element  405  is configured to allow a user to configure characteristics of detectors. The characteristics can be features of preferred content desired and/or undesired by the user. Example characteristics include a detector type such as natural imagery, facial recognition, facial characteristics, and the like. Referring now to  FIG.  4 C , the user interface element  405  is activated, which triggers the user interface  400  to provide user interface elements  430  through  432  that allow users to configure a detector type of the new detector designated by “Saylor Twift.” A detector of a detector type is configured to search for specific features in media content. For example, a detector of a natural imagery is configured to search for images of nature, a detector of a facial recognition is configured to search for images of faces (e.g., male, female, baby, etc.), and a detector of a facial characteristics is configured to search for images of facial characteristics (e.g., brown eyes, blue eyes, red eyes, pale skin, dark skin, etc.) The user interface  400  may provide information directing users to provide example media content items for configuring a detector of a particular detector type that is selected by the user. 
       FIG.  4 D  is an example user interface for users to configure detectors while reviewing search results, according to one embodiment. The media detection system  140  allows users to refine detectors by configuring detectors while reviewing search results generated by the detectors. As described previously, the detector management module  152  updates a detector concurrently when the search engine  148  employs the detector to search for preferred content. The detector management module  152  updates the detector based on user input. The user input is included in the example media content items for configuring the detector. For example, a video frame that is confirmed (disapproved) by a user is included as a positive (negative) example along with other example media content items for training the detector. 
     As illustrated, the media detection system  140  employs the “Saylor Twift” detector configured as illustrated in  FIG.  4 A  to search for the defined preferred content in a video stream. The user interface  450  is configured to display search results for users&#39; review and to receive user input for configuring detectors. As illustrated, the video frame  452  is presented in the display area  451  of the user interface  450 . A user interface element  458  (e.g., a box) indicates to the user the portion of the video frame  452  that is determined to include the preferred content. The user interface element  458  is overlaid over the video frame  452 . In the illustrated example, the box  458  is positioned to surround the individual&#39;s image to indicate to the user that the individual&#39;s image is likely to be Saylor Twift&#39;s image. The user interface element  456  indicates to the user the absolute confidence score of the individual&#39;s image being Saylor Twift&#39;s image and the user interface element  457  indicates to the user the confidence score in a sliding scale. 
     The user interface  450  includes the user interface elements  453  through  455  configured to allow users to provide feedback for configuring detectors while reviewing the search result. The user interface element  453  provides instructions on how to provide feedback. The user interface elements  454  and  455  receive user feedback. The user interface element  454  ( 455 ), if triggered, generates a signal indicating that the video frame  452  is a positive (negative) example. The user interface module  150  provides the user feedback to the detector management module  152  and the detector management module  152  includes video frame  452  in a set of example media content items for creating the detector. In some embodiments, the detector management module  152  includes only the portion that is determined to include the preferred content in the set of example media content items. 
     Example User Interface for Highlighting Searched Content 
       FIGS.  5 A through  5 D  illustrate a user interface for highlighting searched content, according to one embodiment. As illustrated in  FIG.  5 A , the user interface  500  includes a display area  504  for presenting a search result determined to include the preferred content. In the illustrated example, the user configures to search for images of a celebrity&#39;s face. The user interface element  502  illustrates a progress of the search engine  148  searching for the preferred content in the video. The user interface element  503  illustrates temporal locations of the video that are determined to include the preferred content. The user interface element  503  is similar to the user interface element  209  described with respect to  FIGS.  2 A through  2 C  and description is omitted herein. 
     The search engine  148  determines that the image  510  of the individual&#39;s face is likely to be an image of the celebrity&#39;s face. The user interface element  501  is configured to highlight the region of the video frame that is determined to include the preferred content. The user interface element  501  is configured to be overlaid on top of the display area  504 . Multiple user interface elements  501  can be overlaid on top of the display area  504  if the preferred content includes multiple objects (concepts or ideas). A user interface element is configured to highlight an identified object (concept or idea). The user interface module  150  configures the user interface element  501  according to the search engine&#39;s  148  output. In particular, a dimension and a position of the user interface element  501  is configured according to data associated with the identified object&#39;s (concept or idea) that is outputted by the search engine. The user interface element  501  may be further configured to present other information associated with the search such as a confidence score, a time point relative to the beginning of the video, a time stamp, a detector, and the like. 
     The user interface element  501  is configured to track the movement of the corresponding object (concept or idea) across consecutive video frames. As illustrated in  FIGS.  5 A through  5 D , the user interface element  501  tracks the movement of the individual&#39;s face across the frames. In various embodiments, the user interface element  501  is configured to reduce an amount of sudden movement of the user interface element  501  between two consecutive video frames thereby to reduce visual disturbance. For example, for an identified object, the user interface module  150  determines an interpolation function using location data of the object outputted by the search engine  148 . The user interface module  150  determines an interpolated location for the object on a particular video frame using the interpolation function. As illustrated in  FIGS.  5 A through  5 D , the user interface element  501  tracks the movement of the individual&#39;s face. As illustrated in  FIGS.  5 A and  5 C , the user interface element  501  does not entirely enclose the image  510  of the individual&#39;s face because on the locations of the user interface elements  501  are determined according to interpolated location data rather than raw location data. 
     Similar to the example interface  450  illustrated in  FIG.  4 D , the user interface element  501  is configured to receive user feedback for configuring detectors which is used for updating the detector. For example, the user interface element  501  is configured to receive user input including whether to use the image  510  of the individual&#39;s face as a positive example or as a negative example. The detector management module  152  receives the user input and includes the image  510  in the set of example media content items for updating the detector. The detector can be updated concurrently when the detector is employed by the search engine  148  to search for the celebrity&#39;s face (i.e., the preferred content). 
     Example User Interface for Presenting Analytics 
       FIGS.  6 A through  6 F  illustrate example user interfaces for presenting analytics of a video stream, according to one or more embodiments. As previously described, the media detection system  140  generates analytics of a preferred content&#39;s appearance in a video stream. The video stream can be live. The media detection system  140  provides one or more user interfaces for presenting the analytics. 
     As illustrated in  FIG.  6 A , the user interface  600  is configured to present analytics and to receive user input. The user interface  600  allows users to configure and adjust the presentation of the analytics. The user interface  600  includes user interface elements  601  through  607 . The user interface element  601  is configured to present background information of the monitoring such as a detector used to analyze a video stream, a starting time point of the analysis, an end time point of the analysis, a timestamp associated with a most recent event, a status (e.g., monitoring, paused, stopped, error) of the video source, and a status (e.g., monitoring, paused, stopped, error) of the analytics. The user interface elements  602  and  603  are configured to allow users to select a format of analytics to be presented. The user interface element  602  is configured to generate a signal if triggered that causes the user interface module  150  to provide a user interface that presents a particular type of analytics over a calendar. The user interface element  603  is configured to generate another signal if triggered that causes the user interface module  150  to provide a user interface that presents another type of analytics. 
     As illustrated, the user interface element  602  is actuated, and the user interface  606  is displayed. The user interface  606  is embedded in the user interface  600 . Referring now to  FIG.  6 B , the user interface  606  includes user interface elements  607  through  610 . The user interface elements  609  are configured to allow users to configure a number of days included in a calendar view. The calendar view illustrates time in a table where columns of the table correspond to days and rows of the table correspond to time intervals (e.g., hours) in a day. The user interface element  609   a  is configured to generate a signal to include 7 days in the calendar view if triggered and the user interface element  609   b  is configured to generate a signal to include 1 day in the calendar view if triggered. 
     The user interface elements  608  are configured to allow a user to navigate the calendar view. The user interface elements  608  are configured to generate a signal to include a particular time interval (e.g., a particular week, a particular day) in the calendar. 
     The user interface elements  610  are configured to illustrate events. An event represents a presence of a preferred content at a particular time. A particular user interface element  610  illustrates one or more particular events. For example, the user interface element  610   a  represents events between 4:00 AM and 5:00 AM on Monday October 23. The user interface elements  610  are configured such that they present analytics of events, for example, a total count of events in a particular time interval corresponding to a row as illustrated. The user interface elements  610  may be configured to be overlaid on top of or embedded in the calendar view. A user interface elements  610  is positioned to be aligned to a cell on the calendar view that corresponds to the specific time interval. The user interface elements  610  are further configured to allow users to review original footage of events. For example, if the user clicks on the user interface element  610   a , a signal is generated to trigger the user interface module  150  to present footage of the events between 4:00 AM and 5:00 AM on Monday October 23. 
     The user interface elements  607  are configured to allow a user to navigate events. The user interface elements  607  are configured to generate a signal to include events in a particular time interval (e.g., a particular week, a particular day). 
       FIGS.  6 C through  6 E  are described in connection with each other. The user interface element  622  illustrated in  FIG.  6 C  is presented if the user interface element  603  illustrated in  FIG.  6 A  is triggered. The user interface element  622  presents one or more types of analytics for users to select. In the illustrated example, the analytic types include a total count of events within a particular time interval, an accumulated count of events from a starting point, and an average count of events within a particular time interval. 
     The user interface  620  illustrated in  FIG.  6 C  is configured to present a total count of events within a time interval (e.g., a week, two weeks, a month, three months). The user interface element  623  is configured to allow a user to specify the time interval for reviewing the total count of event. The user interface elements  621  are configured to illustrate the total counts of events for different time intervals. In the illustrated example, a trajectory  624  is constructed to connect the user interface elements  621  to illustrate the trend over time. 
     The user interface  630  illustrated in  FIG.  6 D  is configured to present an accumulated count of events from a starting point (e.g., a beginning of a video stream that is being analyzed). The user interface element  631  (e.g., a bar) is configured to illustrate the accumulated count of events. The length of the user interface element  631  is determined according to the accumulated count. In the illustrated example, only one user interface element  631  is illustrated because the preferred content includes only one object (concept or idea). Multiple user interface elements  631  can be included in the user interface  630  to illustrate different objects in the preferred content. The multiple user interface elements  631  may be configured to be visually distinguished from each other. For example, the user interface elements  631  are of different colors, patterns, shades, and the like. 
     The user interface  640  illustrated in  FIG.  6 E  is configured to present an average count of events within the time interval. The user interface element  643  is configured to allow a user to specify the time interval for reviewing the average count of events. The user interface elements (e.g., bars)  641  are configured to illustrate the average counts of events for different time intervals. The length of a user interface element  641  is determined according to the average count. In the illustrated example, only one user interface element  641  is illustrated for each time interval because the preferred content includes only one object (concept or idea). Multiple user interface elements  641  can be included in the user interface  630  in each time interval to illustrate different objects in the preferred content. The multiple user interface elements  641  may be configured to be visually distinguished from each other. For example, the user interface elements  641  are of different colors, patterns, shades, and the like. 
     Example Process Flow 
       FIG.  7    is a flow chart of an example process of playing back a video, according to one embodiment. The media detection system  140  receives  702  a selection of a video for playback from a user. The media detection system  140  generates  704  a user interface for playing the selected video. The user interface includes a progress bar interface element. A location within the progress bar interface element corresponds to a frame of the video. The media detection system  140  provides  706  the generated user interface to a client device associated with the user for display. The media detection system  140  receives  708  a request to search the selected video for a selected object from the user. 
     The media detection system  140  classifies  710  frames of the video using one or more detectors. A detector is configured to process the frame and output a confidence score indicating a likelihood that the selected object is present within the frame. In some embodiments, the media detection system  140  employs a plurality of detectors to classify a video frame. The media detection system  140  determines an average confidence score using the confidence scores classified by the plurality of detectors and associates the average confidence score with the frame. In some embodiments, the media detection system  140  monitors the displayed frame during playback, and provides the confidence score associated with the displayed frame for display in the user interface. The user interface includes a user interface element for displaying the confidence score. 
     The media detection system  140  identifies  712  one or more video segments based on the classification. A video segment comprises a set of consecutive frames associated with confidence scores greater than a threshold confidence score. In some embodiments, a video segment includes at least a minimum threshold number of frames. In some embodiments, the media detection system  140  determines a confidence score for a video segment by averaging confidence scores associated with the video frames included in the video segment. The media detection system  140  selects the video segments of which the associated confidence score is greater than a threshold confidence score. The video segment may include a video frame of which the associated confidence score is less than the threshold confidence score. The video segments may be identified dynamically according to the threshold confidence score input by the user. The user interface includes a user interface element configured to receive the threshold confidence score from the user. 
     The media detection system  140  modifies  714  the displayed progress bar interface element to highlight locations within the progress bar interface element that correspond to the identified one or more video segments. The progress bar interface element may be visually distinguished from the progress bar interface element. For example, the displayed progress bar interface element is in a first color, and the progress bar interface element is in a second color different from the first color. The media detection system  140  may modify the displayed progress bar interface element dynamically according to the threshold confidence score input by the user. 
       FIG.  8    is a flow chart of an example process of updating a detector, according to one embodiment. The media detection system  140  receives  802  a request to identify a selected object in one or more media content items from a user device. The media detection system  140  identifies  804  a set of media content items that include the selected object from the one or more media content items. The media content items are identified by classifying the one or more media content items using a set of detectors configured to identify the selected object within media content items. The set of detectors are trained using a set of example media content items. The media detection system  140  may provide a user interface for users to select the set of example media content items from a plurality of media content items. In some embodiments, the example media content items are retrieved by performing an image search of an image database using keywords corresponding to the selected object. In some embodiments, the example media content items include examples of media content items that do not include the selected object. 
     The media detection system  140  provides  806  the identified set of media content items for display within a user interface on the user device. The media detection system  140  receives  808  a selection of a subset of the displayed media content items from the user device. The media detection system  140  retrains  810  one or more detectors of the set of detectors based on the selected subset of the displayed media content items. The media detection system  140  produces a modified set of example media content items to retrain the one or more detectors. For example, the media detection system  140  removes (or adds) the media content items of the received subset of displayed media content items from the set of example media content items. The received subset of the displayed media content items include examples of media content items that include the selected object. 
       FIG.  9    is a flow chart of an example process of playing back a video, according to one embodiment. The media detection system  140  receives  902  a selection of a video for playback from a user. The media detection system  140  generates  904  a user interface for playing the selected video. The user interface includes a user interface element for displaying the video frame. The media detection system  140  provides  906  the generated user interface to a client device associated with the user for display. The media detection system  140  receives  908  a request to search the selected video for a selected object from the user. 
     The media detection system  140  identifies  910  a set of frames of the selected video that include the selected object by classifying frames of the video using one or more detectors. A detector is configured to 1) identify a presence of the selected object within the frame, 2) determine an associated confidence score indicating a likelihood of the selected object being present within the frame, and 3) identify a location within the frame in which the selected object is located for frames associated with an above-threshold confidence score. 
     The media detection system  140  modifies  912  the video interface element displayed by the client device by highlighting the identified location within the frame in which the selected object is located. The highlighting may be formed for each frame of the identified set of frames displayed within the video interface element. For example, the media detection system  140  overlays one or more user interface elements on top of the video frame thereby to highlight an identified location within a frame in which the selected object is located. The one or more user interface elements include boundary boxes that surround the location within a frame in which the selected object is located. The one or more user interface elements are relocated each time a new frame of the selected video is displayed based on a change in location within the frame in which the selected object is located relative to a previous frame. In cases where a displayed frame includes multiple instances of the object, the media detection system  140  highlights each instance of the object. 
     The media detection system  140  may provide a feedback interface element on the client device that allows users to provide feedback. If receiving feedback via the feedback interface element indicating that a displayed frame with a highlighted identified location does not include the selected object, the media detection system  140  retrains one or more of the detectors employed based on feedback. In some embodiments, the media detection system  140  may provide for display on the client device a confidence interface element configured to display the confidence score associated with a video frame when the video frame is displayed. 
       FIG.  10    is a flow chart of an example process of monitoring a video, according to one embodiment. The media detection system  140  interfaces  1002  with a client device that displays a user interface comprising a schedule representative of a period of time. The schedule is displayed as a set of time intervals within the period of time. The media detection system  140  highlights the time intervals within the set of time intervals that correspond to one or more timestamps of frames within the identified set of frames. A time interval includes one or more of: a day, an hour, an hour within a set of working hours, and a 10-minute interval. 
     The media detection system  140  receives  1004  a request to monitor a video for a selected object. The video includes video frames that each are associated with a timestamp. The media detection system  140  identifies  1006  a set of frames of the video that includes the selected object by. For each of a plurality of frames, the media detection system  140  classifies the frame using a set of detectors configured to output an associated confidence score indicating a likelihood that the frame includes the selected object. The identified set of frames includes frames associated with a confidence score greater than a threshold confidence score. 
     The media detection system  140  identifies  1008  portions of the schedule corresponding to one or more timestamps of frames within the identified set of frames. The media detection system  140  modifies  1010  the user interface displayed by the client device to indicate identified portions of the schedule. The media detection system  140  may indicate within a highlighted time interval a number of occurrences of the selected object within the frames of the identified set of frames associated with timestamps corresponding to the time interval. If the selected object includes a face of a selected person, the media detection system  140  modifies overlays text associated with an identity of the selected person on the portions of the schedule displayed within the user interface. 
     The media detection system  140  may receive a request from a user for a total amount of time within the video in which the selected object is included. The media detection system  140  displays within the second user interface element an amount of time corresponding to a sum of time associated with each identified portion of the schedule. The video may be a live video, and the media detection system  140  modifies the user interface displayed by the client device to indicate identified portions of the schedule in real-time. 
     Computer Architecture 
       FIG.  11    is a high-level block diagram of a computer  1100  for implementing different entities illustrated in  FIG.  1   . The computer  1100  includes at least one processor  1102  coupled to a chipset  1104 . Also coupled to the chipset  1104  are a memory  1106 , a storage device  1108 , a keyboard  1110 , a graphics adapter  1112 , a pointing device  1114 , and a network adapter  1116 . A display  1118  is coupled to the graphics adapter  1112 . In one embodiment, the functionality of the chipset  1104  is provided by a memory controller hub  1120  and an I/O controller hub  1122 . In another embodiment, the memory  1106  is coupled directly to the processor  1102  instead of the chipset  1104 . 
     The storage device  1108  is any non-transitory computer-readable storage medium, such as a hard drive, compact disk read-only memory (CD-ROM), DVD, or a solid-state memory device. The memory  1106  holds instructions and data used by the processor  1102 . The pointing device  1114  may be a mouse, track ball, or other type of pointing device, and is used in combination with the keyboard  1110  to input data into the computer system  1100 . The graphics adapter  1112  displays images and other information on the display  1118 . The network adapter  1116  couples the computer system  1100  to the network  150 . 
     As is known in the art, a computer  1100  can have different and/or other components than those shown in  FIG.  11   . In addition, the computer  1100  can lack certain illustrated components. For example, the computer acting as the online system  100  can be formed of multiple blade servers linked together into one or more distributed systems and lack components such as keyboards and displays. Moreover, the storage device  1108  can be local and/or remote from the computer  1100  (such as embodied within a storage area network (SAN)). 
     As is known in the art, the computer  1100  is adapted to execute computer program modules for providing functionality described herein. As used herein, the term “module” refers to computer program logic utilized to provide the specified functionality. Thus, a module can be implemented in hardware, firmware, and/or software. In one embodiment, program modules are stored on the storage device  1108 , loaded into the memory  1106 , and executed by the processor  1102 . 
     Alternative Embodiments 
     The features and advantages described in the specification are not all inclusive and in particular, many additional features and advantages will be apparent to one of ordinary skill in the art in view of the drawings, specification, and claims. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and may not have been selected to delineate or circumscribe the disclosed subject matter. 
     It is to be understood that the figures and descriptions have been simplified to illustrate elements that are relevant for a clear understanding of the present invention, while eliminating, for the purpose of clarity, many other elements found in a typical online system. Those of ordinary skill in the art may recognize that other elements and/or steps are desirable and/or required in implementing the embodiments. However, because such elements and steps are well known in the art, and because they do not facilitate a better understanding of the embodiments, a discussion of such elements and steps is not provided herein. The disclosure herein is directed to all such variations and modifications to such elements and methods known to those skilled in the art. 
     Some portions of above description describe the embodiments in terms of algorithms and symbolic representations of operations on information. These algorithmic descriptions and representations are commonly used by those skilled in the data processing arts to convey the substance of their work effectively to others skilled in the art. These operations, while described functionally, computationally, or logically, are understood to be implemented by computer programs or equivalent electrical circuits, microcode, or the like. Furthermore, it has also proven convenient at times, to refer to these arrangements of operations as modules, without loss of generality. The described operations and their associated modules may be embodied in software, firmware, hardware, or any combinations thereof. 
     As used herein any reference to “one embodiment” or “an embodiment” means that a particular element, feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment. The appearances of the phrase “in one embodiment” in various places in the specification are not necessarily all referring to the same embodiment. 
     Some embodiments may be described using the expression “coupled” and “connected” along with their derivatives. It should be understood that these terms are not intended as synonyms for each other. For example, some embodiments may be described using the term “connected” to indicate that two or more elements are in direct physical or electrical contact with each other. In another example, some embodiments may be described using the term “coupled” to indicate that two or more elements are in direct physical or electrical contact. The term “coupled,” however, may also mean that two or more elements are not in direct contact with each other, but yet still co-operate or interact with each other. The embodiments are not limited in this context. 
     As used herein, the terms “comprises,” “comprising,” “includes,” “including,” “has,” “having” or any other variation thereof, are intended to cover a non-exclusive inclusion. For example, a process, method, article, or apparatus that comprises a list of elements is not necessarily limited to only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Further, unless expressly stated to the contrary, “or” refers to an inclusive or and not to an exclusive or. For example, a condition A or B is satisfied by any one of the following: A is true (or present) and B is false (or not present), A is false (or not present) and B is true (or present), and both A and B are true (or present). 
     In addition, use of the “a” or “an” are employed to describe elements and components of the embodiments herein. This is done merely for convenience and to give a general sense of the various embodiments. This description should be read to include one or at least one and the singular also includes the plural unless it is obvious that it is meant otherwise. 
     Upon reading this disclosure, those of skill in the art will appreciate still additional alternative designs for a unified communication interface providing various communication services. Thus, while particular embodiments and applications of the present disclosure have been illustrated and described, it is to be understood that the embodiments are not limited to the precise construction and components disclosed herein and that various modifications, changes and variations which will be apparent to those skilled in the art may be made in the arrangement, operation and details of the method and apparatus of the present disclosure disclosed herein without departing from the spirit and scope of the disclosure as defined in the appended claims.