Patent Publication Number: US-10778888-B2

Title: Automatic selection of a camera based on facial detection

Description:
This application is a continuation application claiming priority to Ser. No. 15/477,694, filed Apr. 3, 2017, now U.S. Pat. No. 10,440,261, issued Oct. 8, 2019. 
    
    
     TECHNICAL FIELD 
     The present invention relates to systems and methods of a camera selection system, and more specifically to embodiments of a camera selection system and method that automatically selects an appropriate camera to use for capturing photos and videos. 
     BACKGROUND 
     Many mobile devices and smartphones include a camera on a front of the device and a camera on a rear of the device. The camera on the rear of the device is most often used by the user to take standard photographs. The camera on the front of the device is most often used by the user to take photographs of themselves, known as “selfies.” 
     SUMMARY 
     An embodiment of the present invention relates to a method, and associated computer system and computer program product, for automatically selecting an appropriate camera to use for capturing photos and videos. A processor of a computing system detects that a camera application loaded on the computing system has been opened by a user. A first camera located on a first side of a mobile device and a second camera located on a second side of the mobile device is activated in response to the detecting, the first camera facing a user and being located on a same side as a main display of the mobile device. A feed received from the first camera and a feed received from the second camera is analyzed to detect whether a face is present in a field of view of the first camera or the second camera. The processor determines that the user intends to use the first camera based on a detection of the face in the field of view of the first camera. The second camera is deactivated in response to the determining, and the feed received from the first camera is displayed on the main display of the mobile device for viewing by the user while using the camera application. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  depicts a block diagram of a camera selection system, in accordance with embodiments of the present invention. 
         FIG. 2A  depicts a mobile device having a first camera on a first side of the mobile device, in accordance with embodiments of the present invention. 
         FIG. 2B  depicts a mobile device having a second camera on a second side of the mobile device, in accordance with embodiments of the present invention. 
         FIG. 3  depicts a flow chart of a method for automatically selecting an appropriate camera to use for capturing photos and videos, in accordance with embodiments of the present invention. 
         FIG. 4  depicts a flow chart of a step of the method of  FIG. 3  for analyzing a feed received from the first camera, in accordance with embodiments of the present invention. 
         FIG. 5  illustrates a block diagram of a computer system for the camera selection system of  FIGS. 1-2B , capable of implementing methods for automatically selecting an appropriate camera to use for capturing photos and videos of  FIGS. 3-4 , in accordance with embodiments of the present invention. 
         FIG. 6  depicts a cloud computing environment, in accordance with embodiments of the present invention. 
         FIG. 7  depicts abstraction model layers, in accordance with embodiments of the present invention. 
     
    
    
     DETAILED DESCRIPTION 
     Smartphones, tablets, mobile devices, and the like, that have at least two cameras allow a user to take a normal or standard picture with a camera located on a backside of the device, as well as take a self-portrait photograph, known as a “selfie” with a camera located on a front side of the device. Current devices and methods require a smartphone or mobile device operator to provide instructions to the device as to which camera (e.g. front or rear) to use, based on the type of photo or video the user desires. For example, if the user intends to take a “selfie,” then the user must press a button, touch a screen, or issue a voice command to instruct the device to use the front side camera, which sometimes requires the camera application to swap from a default use of the rear camera to a new use of the front camera. Interacting with the device to provide an instruction or selection of the camera to use the front or rear camera can result in a less than exceptional user experience, and can delay the photograph or video taking. Further, users can miss the button on the screen to switch the camera, or new users of a device may not know where the button is to switch the camera, causing further delays. 
     Thus, a need exists for an automatic camera selection system and method that automatically determines an appropriate camera to use for capturing a photo or video, based on a positioning of the user and/or objects to be captured by the device&#39;s cameras. 
     Referring to the drawings,  FIG. 1  depicts a block diagram of a camera selection system  100 , in accordance with embodiments of the present invention. Embodiments of a camera selection system  100  may include a computing system  120 . Computing system  120  may be a computing system of a mobile device, a smartphone, a cellphone, a tablet, an e-reader, a laptop, a portable device, a portable computing device, a smartwatch, and the like. Embodiments of a camera selection system  100  may comprise a first camera  110  and a second camera  111  coupled to a computing system  120  via an I/O interface  150 . For instance, the first camera  110  and the second camera  111  may be connected via an I/O interface  150  to computer system  120 . The number of cameras  110 ,  111  connecting to computer system  120  via data bus lines  155   a ,  155   b  (referred to collectively as “data bus lines  155 ) may vary from embodiment to embodiment, depending on the number of cameras present on a mobile device or in the camera selection system  100 . 
     As shown in  FIG. 1 , a first camera  110  and a second camera  111  may transmit data, such as photographs, videos, audio/visual content, pixel information, effects, date/time information, etc. (e.g. “camera data”) captured, collected, or otherwise created by the first camera  110  and/or the second camera  111  by connecting to computing system  120  via the data bus lines  155  to an I/O interface  150 . An I/O interface  150  may refer to any communication process performed between the computer system  120  and the environment outside of the computer system  120 , for example, the cameras  110 ,  111 . Input to the computing system  120  may refer to the signals or instructions sent to the computing system  120 , for example the camera data collected by the cameras  110 ,  111 , while output may refer to the signals sent out from the computer system  120  to the cameras  110 ,  111 . 
       FIG. 2A  depicts a mobile device  115  having a first camera  110  on a first side  116  of the mobile device  115 , in accordance with embodiments of the present invention. Embodiments of the first camera  110  may be located on a same side of the mobile device  115  as a main display  118  of the mobile device  115 . The first side  116  of the mobile device  115  may be a front side or surface of the mobile device  115 . For instance, embodiments of the first camera  110  located on a first side  116  of the mobile device  115  may face a user when the user holds, uses, operates, or otherwise manipulates the device  115 , in a convention manner. In an exemplary embodiment, the first camera  110  on the first side  116  of the mobile device  115  may be used to take “selfies.”  FIG. 2B  depicts a mobile device  115  having a second camera  11  on a second side  117  of the mobile device  115 , in accordance with embodiments of the present invention. Embodiments of the second camera  111  may be located on a reverse side of the mobile device  115  as the main display  118  of the mobile device  115 . The second side  117  of the mobile device  115  may be a rear or back side or surface of the mobile device  115 . For instance, embodiments of the second camera  111  located on a second side  117  of the mobile device  115  may face away from a user when the user holds, uses, operates, or otherwise manipulates the device  115 , in a convention manner. In an exemplary embodiment, the second camera  111  on the second side  117  of the mobile device  115  may be used to take a normal or standard photograph or video, (e.g. of people or objects that are facing the user and are a distance away from the user, as the user uses the camera application on the mobile device  115 ). Accordingly, embodiments of the mobile device  115 , which may be computing system  120 , includes two or more cameras, that are located on different or opposite sides of the mobile device  115 . Further, embodiments of the first camera  110  and the second camera  111  may be referred to as a sensor, an input means, an input mechanism, and the like, for capturing audio/visual content, and operated or controlled by a camera software application loaded on the computing system  120 . For example, the computing system  120  may include a camera application that communicates with the cameras  110 ,  111  to provide instruction and command for the operating of the cameras  110 ,  111  as known to those skilled in the art. 
     Referring again to  FIG. 1 , embodiments of the camera selection system  100  may include a server  112  and an associated database  113 . The server  112  may be a remote server associated with a third party camera application that may communicate with the computing system  120  over a network, such as network  107 . Photographs or videos captured by the cameras  110 ,  111  may be transmitted to the server  112  and potentially the database  113  associated with the server  112 . The server  112  may be associated with a third party application that may be loaded on the computing system  120 , but separate from the camera application of the mobile device  115 . For example, the server  112  may service requests made by a third party photo or video application that can operate or otherwise control the cameras  110 ,  111  of the mobile device  115  to take a photograph or video. In an exemplary embodiment, the computing system  120  communicated with the server  112  and/or database  113  over the network  107 . A network  107  may refer to a group of two or more computer systems linked together. Network  107  may be any type of computer network known by individuals skilled in the art. Examples of computer networks  107  may include a LAN, WAN, campus area networks (CAN), home area networks (HAN), metropolitan area networks (MAN), an enterprise network, cloud computing network (either physical or virtual) e.g. the Internet, a cellular communication network such as GSM or CDMA network or a mobile communications data network. The architecture of the computer network  107  may be a peer-to-peer network in some embodiments, wherein in other embodiments, the network  107  may be organized as a client/server architecture. 
     In some embodiments, the network  107  may further comprise, in addition to the computer system  120 , server  112 , and database  113 , a connection to one or more network accessible knowledge bases containing information of one or more users, network repositories  114  or other systems connected to the network  107  that may be considered nodes of the network  107 . In some embodiments, where the computing system  120  or network repositories  114  allocate resources to be used by the other nodes of the network  107 , the computer system  120  and network repository  114  may be referred to as servers. 
     The network repository  114  may be a data collection area on the network  107  which may back up and save all the data transmitted back and forth between the nodes of the network  107 . For example, the network repository  114  may be a data center saving and cataloging camera data sent by the first camera  110  and/or the second camera  111  to generate both historical and predictive analysis of users, and to prepare or create a visual timeline of a user with audio/visual content transmitted by the computing system  120 . In some embodiments, a data collection center housing the network repository  114  may include an analytic module capable of analyzing each piece of data being stored by the network repository  114 . Further, the computer system  120  may be integrated with or as a part of the data collection center housing the network repository  114 . In some alternative embodiments, the network repository  114  may be a local repository (not shown) that is connected to the computer system  120 . 
     Referring still to  FIG. 1 , embodiments of the computing system  120  may receive additional data from one or more sensors  121  which may be positioned within an environment shared by the user, worn by the user, or otherwise disposed in a location that can result in obtaining user data for the detection of a face position of a user and/or proper selection of the camera of the computing system  120 . Sensors  121  may be a sensor, an input device, or any input mechanism. For example, sensor  121  may be a biometric sensor, a wearable sensor, an environmental sensor, a camera, a camcorder, a microphone, a peripheral device, a computing device, a mobile computing device, such as a smartphone or tablet, facial recognition sensor, voice capture device, and the like. Embodiments of sensors  121  may further include sensors either worn or placed in a user environment or public environment that the user may be located, such as a kitchen, bedroom, living room, bar, dance club, festival, attraction, and the like. Further embodiments of sensors  121  may include one or more input devices or input mechanisms, including one or more cameras positioned proximate the user or within an environment shared by the user. The one or more cameras (i.e. in addition to or separate from the first camera  110  and second camera  111 ) may capture image data or video data of a user, including a posture, a facial expression, a gesture, etc., which may be used to assist in the determination of which camera  110 ,  111  to use. Embodiments of the sensors  121  may also include one or more microphones positioned nearby the user to collect audio relating to the user, which may listen for keyword triggers, such as “selfie” to assist in the determination of which camera  110 ,  111  to use. 
     Some or all of the sensors  121  may transmit user data to computing system  120  over network  107 . In other embodiments, the sensors  121  may transmit data via data bus lines directly to the computing system  120 . Furthermore, embodiments of computing system  120  may communicate with various applications that contain data about the user to also assist in the determination of which camera  110 ,  111  to use. 
     Embodiments of the computer system  120  may be equipped with a memory device  142  which may store the camera data, sensor data, and/or user data, and a processor  141  for implementing the tasks associated with the camera selection system  100 . In some embodiments, one or more camera applications may be loaded in the memory  142  of the computer system  120 . Further, in some embodiments, a camera selection application  130  may be loaded into the memory  142  of the computing system  120 . The computing system  120  may further include an operating system, which can be a computer program for controlling an operation of the computing system  120 , wherein applications loaded onto the computing device  120  may run on top of the operating system to provide various functions. 
     With continued reference to  FIG. 1 , embodiments of computer system  120  may include a camera selection application or module  130 . Embodiments of the computing system  120  may include an application module  131 , an activation module  132 , an analytics module  133 , and a viewing module  134 . A “module” may refer to a hardware based module, software based module or a module may be a combination of hardware and software. Embodiments of hardware based modules may include self-contained components such as chipsets, specialized circuitry and one or more memory devices, while a software-based module may be part of a program code or linked to the program code containing specific programmed instructions, which may be loaded in the memory device of the computer system  120 . A module (whether hardware, software, or a combination thereof) may be designed to implement or execute one or more particular functions or routines. 
     Embodiments of the application module  131  may include one or more components of hardware and/or software program code for detecting that a camera application loaded on the computing system  120  has been opened by a user. For instance, when a user decides to take a photograph or video, the user may open or otherwise run or activate a camera application on the user&#39;s mobile device. Embodiments of the detection module  131  may detect or otherwise become aware that one camera application of potentially a plurality of camera applications has been opened and seeks to initiate control of the first camera  110  and/or second camera  111 . 
     Further, embodiments of the computing system  120  of the camera selection system  100  may include an activation module  132 . Embodiments of the activation module  132  may include one or more components of hardware and/or software program code for activating the first camera  110  located on a first side  116  of a mobile device  115  and a second camera  111  located on a second side  117  of the mobile device  115 . The activation module  132  may activate or otherwise initiate the first camera  110  and the second camera  111  in response to the detecting of the camera application being opened by the application module  131 . Embodiments of the activation module  132  may activate the first camera  110  and the second camera  111  simultaneously, or may activate the cameras sequentially. Further, embodiments of the activation module  132  may activate one or more sensors  121  in communication with the computing system  120 , also in response to the detection of the camera application being opened by the application module  131 . The activation module  132  may determine which sensors  121  are located nearby or within a same environment as the user when the user opens the camera application. For instance, the activation module  132  may activate or sync with sensors  121  that are capable of providing data that may assist in the current determination of which camera that the camera selection module  130  should use. Further, the activation module  132  may synchronize the sensors  121  and the cameras  110 ,  111  so that data being transmitted back and forth is accurate and relevant. 
     Embodiments of the computing system  120  of the camera selection system  100  may include an analytics module  133 . Embodiments of the analytics module  133  may include one or more components of hardware and/or software program code for analyzing a feed received from the first camera  110  and a feed received from the second camera  111  to detect whether a face is present in a field of view of the first camera  110  or the second camera  111 . For instance, in response to being activated, the first camera  110  may transmit a live feed data to the computing system  120 . The live feed may include a stream of data being transmitted from the first camera  110  to the computing system  120 , wherein the live feed may include objects captured by the camera  110  within a field of view of the first camera  110 . Embodiments of the analytics module  133  may analyze, scan, review, etc. the feed received from the first camera  110  to detect one or more faces of a user. In an exemplary embodiment, the analytics module  133  may utilize a face detection technology identify and/or detect a human face in a digital image included in the feed received from the first camera  110 . The analytics module  133  may use an object-class detection technique having an algorithm that can detect a face of a user. In further embodiments, the analytics module  133  may also use a facial recognition system to detect and/or identify not only human faces, but the exact face of the user of the mobile device  115 . For instance, the analytics module  133  may analyze the feed received from the first camera  110  and detect whether a human face is present within the field of view of the first camera  110 , and may also identify and confirm that the face present within the field of view is that of the user operating the mobile device  115 . 
     Likewise, embodiments of the analytics module  133  may analyze the feed received from the second camera  111 . The analyzing by the analytics module  133  of the feed from the first camera  110  and the feed from the second camera  111  may be performed simultaneously. Alternatively, the analytics module  133  may first analyze the feed received from the first camera  110 , and then the feed received from the second camera  111 , or vice versa. In response to being activated, the second camera  111  may transmit a live feed data to the computing system  120 . The live feed may include a stream of data being transmitted from the second camera  111  to the computing system  120 , wherein the live feed may include objects captured by the second camera  111  within a field of view of the second camera  111 . Embodiments of the analytics module  133  may analyze, scan, review, etc. the feed received from the second camera  111  to detect one or more faces of a user. In an exemplary embodiment, the analytics module  133  may utilize a face detection technology identify and/or detect a human face in a digital image included in the feed received from the second camera  111 . The analytics module  133  may use an object-class detection technique having an algorithm that can detect a face of a user. In further embodiments, the analytics module  133  may also use a facial recognition system to detect and/or identify not only human faces, but the exact face of the user of the mobile device  115 . For instance, the analytics module  133  may analyze the feed received from the second camera  111  and detect whether a human face is present within the field of view of the second camera  111 , and may also identify and confirm that the face present within the field of view is that of the user operating the mobile device  115 . 
     Furthermore, embodiments of the analytics module  133  may detect whether a face is present in a field of view of the first camera  110  or the second camera  111 , and determine which of the first camera  110  or the second camera  111  (or any additional cameras associated with the computing system  120 ) that the user intends to use or should use. Embodiments of the analytics module  133  may determine that the user intends to use the first camera  110  based on a detection of the face in the field of view of the first camera  110 , as a result of analyzing the feeds from the first camera  110  and/or the second camera  111 . If the analytics module  133  detects a face of the user operating the mobile device  115  within the field of the view of the first camera  110 , then the analytics module  133  may determine that the user intends to take a “selfie.” In this embodiment, the viewing module  134  may deactivate the second camera  111  and display the feed received from the first camera  110  on the display  118  of the mobile device, as described in greater detail infra. In an exemplary embodiment, the analytics module  133 , prior to a deactivating of the second camera  111  and displaying of the feed from the first camera  110 , may confirm, that the user intends to use the first camera  110  by detecting an object placed over or partially over the second camera  111 . For instance, the analytics module  133 , by analyzing the feed from the second camera  111 , may detect an object, such as a hand, a finger, or thumb of the user over or partially over the second camera  111  as the user holds the mobile device  115  while using the camera application. If the object is detected, the determination may be confirmed because the user is holding the mobile device  115  in such a way to take a “selfie” (e.g. cupping the mobile device  115  within the user&#39;s hand). 
     Furthermore, embodiments of the analytics module  133  may optionally perform further analyzing of the feed received from the first camera  110 , in response to a detection of a face within the field of view of the first camera  110 . For example, the analytics module  133  may determine whether the face is within a predefined proximity to the mobile device  115 . If the face of the user is within a certain distance from the mobile device (e.g. 3 feet or closer), then the analytics module  133  may determine that the user intends to take a “selfie,” and may select the first camera  110  for use by the camera application. Alternatively, if the face is outside the predetermined proximity, then the analytics module  133  may determine that the user does not intend to take a “selfie,” and may select the second camera  111  for use by the camera application. Various different proximities and rules associated with the proximities may vary, such that the selection of the first camera  110  or the second camera  111  may vary depending on the desired proximity and proximity rules. Moreover, the analytics module  133  may also determine whether the detected face is viewed from a point of above the face. In other words, the analytics module  133  may determine whether the mobile device  115  is elevated above the user&#39;s face such that the perspective from the first camera  110  shows a front, elevated view of the user&#39;s face, as is common with many “selfie” pictures. Additionally, the analytics module  133  may also identify that the face detected is the face of the user, using facial recognition technology. For instance, if the face detected is not the user, then the analytics module  133  may determine that another user is using the mobile device to take a standard photograph of the user. Accordingly, embodiments of the analytics module  133  may determine that the user intends to take a “selfie” and select the first camera  110  for use when a face is detected within the field of view of the first camera  110 , the face is within (or outside depending on the proximity rule) a predetermined proximity to the mobile device  115 , the camera  110  is positioned above the face, and/or the facial identity of the user is confirmed using facial recognition technology. 
     If the analytics module  133  does not detect a face within the field of view of the first camera  110 , then the analytics module  133  may determine that the user intends to take a standard photograph or video, and the viewing module  134  may deactivate the first camera  110  and display the feed received from the second camera  111  on the display  118  of the mobile device  115 , as described in greater detail infra. 
     Continuing to refer to  FIG. 1 , embodiments of the computing system  120  may include a viewing module  134 . Embodiments of the viewing module  134  may include one or more components of hardware and/or software program code for deactivating one of the first camera  110  and the second camera  111 , and displaying, the feed received from the first camera  110  or the second camera  111  on the main display  118  of the mobile device  115  for viewing by the user while using the camera application. Embodiments of the viewing module  134  may deactivate the second camera  111  in response to a determination that the user intends to take a “selfie” and intends to use the first camera  110 , and may also display the feed received from the first camera  110  on the main display  118  of the mobile device  115 . Alternatively, embodiments of the viewing module  134  may deactivate the first camera  110  in response to a determination that the user intends to take a standard picture or video and intends to use the second camera  111 , and may also display the feed received from the second camera  111  on the display  118  of the mobile device  115 . 
     In a different embodiment, the viewing module  134  may display both the feed from the first camera  110  and the second camera  111 , in response to the activation module  131  activating the first camera  110  and the second camera  111  when a camera application has been opened. For instance, the viewing module  134  may display the feeds side-by-side on the display  118  so that the user may select which camera to use. 
     Referring now to  FIG. 3 , which depicts a flow chart of a method  200  method for automatically selecting an appropriate camera to use for capturing photos and videos, in accordance with embodiments of the present invention. One embodiment of a method  200  or algorithm that may be implemented method for automatically selecting an appropriate camera to use for capturing photos and videos in accordance with the camera selection system  100  described in  FIGS. 1-2  using one or more computer systems as defined generically in  FIG. 5  below, and more specifically by the specific embodiments of  FIGS. 1-2B . 
     Embodiments of the method  200  method for automatically selecting an appropriate camera to use for capturing photos and videos may begin at step  201  wherein a camera application being opened by the user is detected. Step  202  activates the cameras associated with the mobile device  115 , such as the first camera  110  and the second camera  111 . The activation of the cameras  110 ,  111  may be done in response to the detection that the camera application has been opened. Step  203  analyzes the feed received from the first camera  110  and the feed received from the second camera  111 .  FIG. 4  depicts a flow chart  300  of a step  203  of the method  200  of  FIG. 3  for analyzing a feed received from the first camera  110 , in accordance with embodiments of the present invention. Step  301  receives a feed from the first and second cameras  110 ,  111 . Step  302  determines whether the feed from the first camera  110  contain a face. If the feed from the first camera  110  does not contain a face, such that no face is detected by the computing system  120 , then step  303  determines that the user intends to the use the second camera  111  for a standard picture. If the feed from the first camera  110  contains a face, such that a face is detected by the computing system  120 , then step  304  may further analyze the feed from the first camera  110 . Step  305  determines whether the detected face is within a predefined proximity with the camera  110 , or whether the proximity to the camera is in accordance with proximity rules. For instance, step  305  determines whether the detected face is between 12-36 inches from the camera  110 . If the face is not within the predetermined proximity or in compliance with proximity rules, then it is determined that the user intends to the use the second camera  111  for a standard picture, as shown in step  303 . If the face is within the predetermined proximity and/or complies with proximity rules, then step  306  determines whether the detected face is positioned below the camera  110 . In other words, step  306  determines whether the mobile device has been elevated with respect to an eye level of the user. If the face is not positioned below the camera  110 , then it is determined that the user intends to the use the second camera  111  for a standard picture, as shown in step  303 . If the face is positioned below the camera  110 , then step  307  confirms that the detected face is the face of the user. For example, step  307  may use facial recognition technology to confirm that the detected face is the face of the user, and not another user operating the camera  110 . If the facial identity of the user is not confirmed, then it is determined that the user intends to the use the second camera  111  for a standard picture, as shown in step  303 . If the facial identity of the detected face is confirmed to be the face of the user, then step  308  determines that the user intends to the use the first camera  110  and that the user intends to take a “selfie.” In an exemplary embodiment, steps  304 - 307  are optionally performed as part of a further analysis, wherein if the feed from the first camera  110  contains a face, such that a face is detected by the computing system  120 , then steps  304 - 307  may be skipped, and the method  300  may move directly to step  308 , which determines that the user intends to the use the first camera  110  and that the user intends to take a “selfie.” 
     Referring back to  FIG. 3 , embodiments of method  200  may include a step  204  that determines, based on the analyzing in step  203 , that the user intends to use the first camera  110  (or the second camera  111 ). Step  205  deactivates the second camera  111  (or the first camera  110  if the determining step  204  determines that the user intends to use the second camera  111 ). Step  206  displays the feed received from the first camera  110  on the display  118  of the mobile device  115  so that the user may take the intended photograph or video (or displays the feed received from the second camera  111  if the determining step  204  determines that the user intends to use the second camera  111 ). 
       FIG. 5  illustrates a block diagram of a computer system for the camera selection system of  FIGS. 1-2B , capable of implementing methods for automatically selecting an appropriate camera to use for capturing photos and videos of  FIGS. 3-4 , in accordance with embodiments of the present invention. The computer system  500  may generally comprise a processor  591 , an input device  592  coupled to the processor  591 , an output device  593  coupled to the processor  591 , and memory devices  594  and  595  each coupled to the processor  591 . The input device  592 , output device  593  and memory devices  594 ,  595  may each be coupled to the processor  591  via a bus. Processor  591  may perform computations and control the functions of computer  500 , including executing instructions included in the computer code  597  for the tools and programs capable of implementing a method for automatically selecting an appropriate camera to use for capturing photos and videos, in the manner prescribed by the embodiments of  FIGS. 3-4  using the camera selection system of  FIGS. 1-2 , wherein the instructions of the computer code  597  may be executed by processor  591  via memory device  595 . The computer code  597  may include software or program instructions that may implement one or more algorithms for implementing the methods for automatically selecting an appropriate camera to use for capturing photos and videos, as described in detail above. The processor  591  executes the computer code  597 . Processor  591  may include a single processing unit, or may be distributed across one or more processing units in one or more locations (e.g., on a client and server). 
     The memory device  594  may include input data  596 . The input data  596  includes any inputs required by the computer code  597 . The output device  593  displays output from the computer code  597 . Either or both memory devices  594  and  595  may be used as a computer usable storage medium (or program storage device) having a computer readable program embodied therein and/or having other data stored therein, wherein the computer readable program comprises the computer code  597 . Generally, a computer program product (or, alternatively, an article of manufacture) of the computer system  500  may comprise said computer usable storage medium (or said program storage device). 
     Memory devices  594 ,  595  include any known computer readable storage medium, including those described in detail below. In one embodiment, cache memory elements of memory devices  594 ,  595  may provide temporary storage of at least some program code (e.g., computer code  597 ) in order to reduce the number of times code must be retrieved from bulk storage while instructions of the computer code  597  are executed. Moreover, similar to processor  591 , memory devices  594 ,  595  may reside at a single physical location, including one or more types of data storage, or be distributed across a plurality of physical systems in various forms. Further, memory devices  594 ,  595  can include data distributed across, for example, a local area network (LAN) or a wide area network (WAN). Further, memory devices  594 ,  595  may include an operating system (not shown) and may include other systems not shown in  FIG. 5 . 
     In some embodiments, the computer system  500  may further be coupled to an Input/output (I/O) interface and a computer data storage unit. An I/O interface may include any system for exchanging information to or from an input device  592  or output device  593 . The input device  592  may be, inter alia, a keyboard, a mouse, etc. or in some embodiments the sensors  110 . The output device  593  may be, inter alia, a printer, a plotter, a display device (such as a computer screen), a magnetic tape, a removable hard disk, a floppy disk, etc. The memory devices  594  and  595  may be, inter alia, a hard disk, a floppy disk, a magnetic tape, an optical storage such as a compact disc (CD) or a digital video disc (DVD), a dynamic random access memory (DRAM), a read-only memory (ROM), etc. The bus may provide a communication link between each of the components in computer  500 , and may include any type of transmission link, including electrical, optical, wireless, etc. 
     An I/O interface may allow computer system  500  to store information (e.g., data or program instructions such as program code  597 ) on and retrieve the information from computer data storage unit (not shown). Computer data storage unit includes a known computer-readable storage medium, which is described below. In one embodiment, computer data storage unit may be a non-volatile data storage device, such as a magnetic disk drive (i.e., hard disk drive) or an optical disc drive (e.g., a CD-ROM drive which receives a CD-ROM disk). In other embodiments, the data storage unit may include a knowledge base or data repository  125  as shown in  FIG. 1 . 
     As will be appreciated by one skilled in the art, in a first embodiment, the present invention may be a method; in a second embodiment, the present invention may be a system; and in a third embodiment, the present invention may be a computer program product. Any of the components of the embodiments of the present invention can be deployed, managed, serviced, etc. by a service provider that offers to deploy or integrate computing infrastructure with respect to camera selection systems and methods. Thus, an embodiment of the present invention discloses a process for supporting computer infrastructure, where the process includes providing at least one support service for at least one of integrating, hosting, maintaining and deploying computer-readable code (e.g., program code  597 ) in a computer system (e.g., computer  500 ) including one or more processor(s)  591 , wherein the processor(s) carry out instructions contained in the computer code  597  causing the computer system to automatically select an appropriate camera to use for capturing photos and videos. Another embodiment discloses a process for supporting computer infrastructure, where the process includes integrating computer-readable program code into a computer system including a processor. 
     The step of integrating includes storing the program code in a computer-readable storage device of the computer system through use of the processor. The program code, upon being executed by the processor, implements a method for automatically selecting an appropriate camera to use for capturing photos and videos. Thus, the present invention discloses a process for supporting, deploying and/or integrating computer infrastructure, integrating, hosting, maintaining, and deploying computer-readable code into the computer system  500 , wherein the code in combination with the computer system  500  is capable of performing a method for automatically selecting an appropriate camera to use for capturing photos and videos. 
     A computer program product of the present invention comprises one or more computer readable hardware storage devices having computer readable program code stored therein, said program code containing instructions executable by one or more processors of a computer system to implement the methods of the present invention. 
     A computer system of the present invention comprises one or more processors, one or more memories, and one or more computer readable hardware storage devices, said one or more hardware storage devices containing program code executable by the one or more processors via the one or more memories to implement the methods of the present invention. 
     The present invention may be a system, a method, and/or a computer program product at any possible technical detail level of integration. The computer program product may include a computer readable storage medium (or media) having computer readable program instructions thereon for causing a processor to carry out aspects of the present invention. 
     The computer readable storage medium can be a tangible device that can retain and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of the computer readable storage medium includes the following: a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanically encoded device such as punch-cards or raised structures in a groove having instructions recorded thereon, and any suitable combination of the foregoing. A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire. 
     Computer readable program instructions described herein can be downloaded to respective computing/processing devices from a computer readable storage medium or to an external computer or external storage device via a network, for example, the Internet, a local area network, a wide area network and/or a wireless network. The network may comprise copper transmission cables, optical transmission fibers, wireless transmission, routers, firewalls, switches, gateway computers and/or edge servers. A network adapter card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium within the respective computing/processing device. 
     Computer readable program instructions for carrying out operations of the present invention may be assembler instructions, instruction-set-architecture (ISA) instructions, machine instructions, machine dependent instructions, microcode, firmware instructions, state-setting data, configuration data for integrated circuitry, or either source code or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, C++, or the like, and procedural programming languages, such as the “C” programming language or similar programming languages. The computer readable program instructions may execute entirely on the user&#39;s computer, partly on the user&#39;s computer, as a stand-alone software package, partly on the user&#39;s computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user&#39;s computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, programmable logic circuitry, field-programmable gate arrays (FPGA), or programmable logic arrays (PLA) may execute the computer readable program instructions by utilizing state information of the computer readable program instructions to personalize the electronic circuitry, in order to perform aspects of the present invention. 
     Aspects of the present invention are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer readable program instructions. 
     These computer readable program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, a programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable storage medium having instructions stored therein comprises an article of manufacture including instructions which implement aspects of the function/act specified in the flowchart and/or block diagram block or blocks. 
     The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable apparatus or other device to produce a computer implemented process, such that the instructions which execute on the computer, other programmable apparatus, or other device implement the functions/acts specified in the flowchart and/or block diagram block or blocks. 
     The flowchart and block diagrams in the Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the Figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts or carry out combinations of special purpose hardware and computer instructions. 
     It is to be understood that although this disclosure includes a detailed description on cloud computing, implementation of the teachings recited herein are not limited to a cloud computing environment. Rather, embodiments of the present invention are capable of being implemented in conjunction with any other type of computing environment now known or later developed. 
     Cloud computing is a model of service delivery for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or interaction with a provider of the service. This cloud model may include at least five characteristics, at least three service models, and at least four deployment models. 
     Characteristics are as follows: 
     On-demand self-service: a cloud consumer can unilaterally provision computing capabilities, such as server time and network storage, as needed automatically without requiring human interaction with the service&#39;s provider. 
     Broad network access: capabilities are available over a network and accessed through standard mechanisms that promote use by heterogeneous thin or thick client platforms (e.g., mobile phones, laptops, and PDAs). 
     Resource pooling: the provider&#39;s computing resources are pooled to serve multiple consumers using a multi-tenant model, with different physical and virtual resources dynamically assigned and reassigned according to demand. There is a sense of location independence in that the consumer generally has no control or knowledge over the exact location of the provided resources but may be able to specify location at a higher level of abstraction (e.g., country, state, or datacenter). 
     Rapid elasticity: capabilities can be rapidly and elastically provisioned, in some cases automatically, to quickly scale out and rapidly released to quickly scale in. To the consumer, the capabilities available for provisioning often appear to be unlimited and can be purchased in any quantity at any time. 
     Measured service: cloud systems automatically control and optimize resource use by leveraging a metering capability at some level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, and active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency for both the provider and consumer of the utilized service. 
     Service Models are as follows: 
     Software as a Service (SaaS): the capability provided to the consumer is to use the provider&#39;s applications running on a cloud infrastructure. The applications are accessible from various client devices through a thin client interface such as a web browser (e.g., web-based e-mail). The consumer does not manage or control the underlying cloud infrastructure including network, servers, operating systems, storage, or even individual application capabilities, with the possible exception of limited user-specific application configuration settings. 
     Platform as a Service (PaaS): the capability provided to the consumer is to deploy onto the cloud infrastructure consumer-created or acquired applications created using programming languages and tools supported by the provider. The consumer does not manage or control the underlying cloud infrastructure including networks, servers, operating systems, or storage, but has control over the deployed applications and possibly application hosting environment configurations. 
     Infrastructure as a Service (IaaS): the capability provided to the consumer is to provision processing, storage, networks, and other fundamental computing resources where the consumer is able to deploy and run arbitrary software, which can include operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure but has control over operating systems, storage, deployed applications, and possibly limited control of select networking components (e.g., host firewalls). 
     Deployment Models are as follows: 
     Private cloud: the cloud infrastructure is operated solely for an organization. It may be managed by the organization or a third party and may exist on-premises or off-premises. 
     Community cloud: the cloud infrastructure is shared by several organizations and supports a specific community that has shared concerns (e.g., mission, security requirements, policy, and compliance considerations). It may be managed by the organizations or a third party and may exist on-premises or off-premises. 
     Public cloud: the cloud infrastructure is made available to the general public or a large industry group and is owned by an organization selling cloud services. 
     Hybrid cloud: the cloud infrastructure is a composition of two or more clouds (private, community, or public) that remain unique entities but are bound together by standardized or proprietary technology that enables data and application portability (e.g., cloud bursting for load-balancing between clouds). 
     A cloud computing environment is service oriented with a focus on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that includes a network of interconnected nodes. 
     Referring now to  FIG. 6 , illustrative cloud computing environment  50  is depicted. As shown, cloud computing environment  50  includes one or more cloud computing nodes  10  with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA) or cellular telephone  54 A, desktop computer  54 B, laptop computer  54 C, and/or automobile computer system  54 N may communicate. Nodes  10  may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud computing environment  50  to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices  54 A,  54 B,  54 C and  54 N shown in  FIG. 6  are intended to be illustrative only and that computing nodes  10  and cloud computing environment  50  can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser). 
     Referring now to  FIG. 7 , a set of functional abstraction layers provided by cloud computing environment  50  (see  FIG. 6 ) is shown. It should be understood in advance that the components, layers, and functions shown in  FIG. 7  are intended to be illustrative only and embodiments of the invention are not limited thereto. As depicted, the following layers and corresponding functions are provided: 
     Hardware and software layer  60  includes hardware and software components. Examples of hardware components include: mainframes  61 ; RISC (Reduced Instruction Set Computer) architecture based servers  62 ; servers  63 ; blade servers  64 ; storage devices  65 ; and networks and networking components  66 . In some embodiments, software components include network application server software  67  and database software  68 . 
     Virtualization layer  70  provides an abstraction layer from which the following examples of virtual entities may be provided: virtual servers  71 ; virtual storage  72 ; virtual networks  73 , including virtual private networks; virtual applications and operating systems  74 ; and virtual clients  75 . 
     In one example, management layer  80  may provide the functions described below. Resource provisioning  81  provides dynamic procurement of computing resources and other resources that are utilized to perform tasks within the cloud computing environment. Metering and Pricing  82  provide cost tracking as resources are utilized within the cloud computing environment, and billing or invoicing for consumption of these resources. In one example, these resources may include application software licenses. Security provides identity verification for cloud consumers and tasks, as well as protection for data and other resources. User portal  83  provides access to the cloud computing environment for consumers and system administrators. Service level management  84  provides cloud computing resource allocation and management such that required service levels are met. Service Level Agreement (SLA) planning and fulfillment  85  provide pre-arrangement for, and procurement of, cloud computing resources for which a future requirement is anticipated in accordance with an SLA. 
     Workloads layer  90  provides examples of functionality for which the cloud computing environment may be utilized. Examples of workloads and functions which may be provided from this layer include: mapping and navigation  91 ; software development and lifecycle management  92 ; virtual classroom education delivery  93 ; data analytics processing  94 ; transaction processing  95 ; camera selection based on a type of photo to be taken 96. 
     The descriptions of the various embodiments of the present invention have been presented for purposes of illustration, but are not intended to be exhaustive or limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments. The terminology used herein was chosen to best explain the principles of the embodiments, the practical application or technical improvement over technologies found in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein