Patent Publication Number: US-2015074206-A1

Title: Method and apparatus for providing participant based image and video sharing

Description:
The present disclosure relates generally to communication networks and, more particularly, to systems and methods for supporting and enabling sharing of media among participants. 
     BACKGROUND 
     Wireless network providers currently enable users to capture media on wireless endpoint devices and to share the media with others. For example, many mobile phones are now equipped with integrated digital cameras for capturing still pictures and short video clips. In addition, many mobile phones are equipped to also store audio recordings. Wireless network providers, e.g., cellular network providers, allow users to send picture, video or audio messages to other users on the same wireless network or even on different networks. In addition, users may share media more directly with one another via peer-to-peer/near-field communication methods. For example, the user may send pictures or video as email attachments, multimedia messages (MMS), or may send a link with a Uniform Resource Locator (URL) for the location of the media via email or instant message to others. However, the user must know beforehand the others with whom the user wishes to share the media and must know how to reach the others, e.g., via an email address, a telephone number, a mobile phone number, etc. 
     SUMMARY 
     In one embodiment, the present disclosure discloses a method for forwarding a media content. For example, the method identifies a known participant captured in the media content, detects an unknown participant captured in the media content and sends a request to a device of the known participant to identify the unknown participant and to provide contact information for the unknown participant. The method then receives from the device of the known participant, the contact information for the unknown participant and sends the media content to a device of the unknown participant using the contact information. 
     In another embodiment, the present disclosure discloses an additional method for forwarding a media content. For example, the method is executed by a processor that identifies a known participant captured in the media content, detects an unknown participant captured in the media content and obtains biometric data and contact information for a plurality of contacts that include the unknown participant. The biometric data and contact information for the plurality of contacts is obtained wirelessly from a device of the known participant that is proximate to the processor. The processor then identifies the unknown participant in the media content using the biometric data that is obtained wirelessly and sends the media content to a device of the unknown participant that is identified using the contact information. 
     In still another embodiment, the present disclosure discloses a further method for forwarding a media content. For example, the method identifies a known participant captured in the media content, detects an unknown participant captured in the media content and obtains biometric data and contact information for a plurality of contacts that include the unknown participant. The biometric data and contact information is obtained from a server of a social network that provides biometric data of contacts who are first and second degree contacts of a user of a device that includes the processor. The known participant is a first degree contact of the user, the unknown participant is a first degree contact of the known participant, and the unknown participant is a second degree contact of the user via the known participant. The method then identifies the unknown participant in the media content using the biometric data that is obtained from the server of the social network and sends the media content to a device of the unknown participant that is identified using the contact information. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The teaching of the present disclosure can be readily understood by considering the following detailed description in conjunction with the accompanying drawings, in which: 
         FIG. 1  illustrates an exemplary network related to the present disclosure; 
         FIG. 2  illustrates a flowchart of a method for sharing a media content, in accordance with the present disclosure; 
         FIG. 3  illustrates a flowchart of another method for sharing a media content, in accordance with the present disclosure; 
         FIG. 4  illustrates a flowchart of still another method for sharing a media content, in accordance with the present disclosure; and 
         FIG. 5  illustrates a high-level block diagram of a general-purpose computer suitable for use in performing the functions described herein. 
     
    
    
     To facilitate understanding, identical reference numerals have been used, where possible, to designate identical elements that are common to the figures. 
     DETAILED DESCRIPTION 
     The present disclosure broadly discloses methods, non-transitory computer-readable media and devices for sharing media. Although the present disclosure is discussed below in the context of wireless access networks and an Internet Protocol (IP) network, the present disclosure is not so limited. Namely, the present disclosure can be applied to packet switched or circuit switched networks in general, e.g., Voice over Internet Protocol (VoIP) networks, Service over Internet Protocol (SoIP) networks, Asynchronous Transfer Mode (ATM) networks, Frame Relay networks, and the like. 
     In one embodiment, the present disclosure is an endpoint device or network server-based method for sharing captured media content among participants. For example, a picture, video or audio recording is captured by an endpoint device and may include the images, likenesses or voices of various participants. The participants captured in the media content may be contacts of, or otherwise socially connected to a user of the device on which the media content is captured. Using biometric data of contacts of the user, the participants in the media content are automatically identified. For example, facial recognition techniques or voice matching techniques may be utilized. Thereafter, the media content can be shared with the identified participants captured in the media content. The user of the device on which the media content is captured or recorded may, over time build up biometric profiles of his or her contacts to enable the automatic identification of participants in the captured or recorded media content. Alternatively, or in addition, a network-based server, such as a server of a social network provider or a server of a communication network provider, may build and store biometric profiles of members of the social network or of network subscribers that can be used to identify participants in the media content. Accordingly, the identification of participants in the media content may be performed locally on an endpoint device that records the media content or within a network to which the media content is uploaded by a user. Additional techniques to help identify unknown participants are described in greater detail below in connection with the exemplary embodiments. 
     To better understand the present disclosure,  FIG. 1  illustrates in greater detail an exemplary system  100  for sharing media content according to the present disclosure. As shown in  FIG. 1 , the system  100  connects endpoint devices  170 ,  171  and  172  with one or more application servers via a core internet protocol (IP) network  110 , a cellular access network  140 , an access network  150  (e.g., Wireless Fidelity (Wi-Fi), IEEE 802.11 and the like) and/or Internet  180 . The system  100  also includes a social network  130  for providing social network profile information regarding members of the social network. 
     In one embodiment, access network  150  may comprise a non-cellular access network such as a wireless local area network (WLAN) and/or an IEEE 802.11 network having a wireless access point  155 , a “wired” access network, e.g., a local area network (LAN), an enterprise network, a metropolitan area network (MAN), a digital subscriber line (DSL) network, a cable network, and so forth. As such, endpoint devices  170 ,  171  and/or  172  may each comprise a mobile phone, smart phone, email device, tablet, messaging device, Personal Digital Assistant (PDA), a personal computer, a laptop computer, a Wi-Fi device, a server (e.g., a web server), and so forth. In one embodiment, one or more of endpoint devices  170 ,  171  and/or  172  are equipped with digital cameras, video capture devices and/or microphones or other means of audio capture/recording in order to support various functions described herein. 
     In one embodiment, cellular access network  140  may comprise a radio access network implementing such technologies as: global system for mobile communication (GSM), e.g., a base station subsystem (BSS), or IS-95, a universal mobile telecommunications system (UMTS) network employing wideband code division multiple access (WCDMA), or a CDMA3000 network, among others. In other words, cellular access network  140  may comprise an access network in accordance with any “second generation” (2G), “third generation” (3G), “fourth generation” (4G), Long Term Evolution (LTE) or any other yet to be developed future wireless/cellular network technology. While the present disclosure is not limited to any particular type of wireless access network, in the illustrative embodiment, wireless access network  140  is shown as a UMTS terrestrial radio access network (UTRAN) subsystem. Thus, element  145  may comprise a Node B or evolved Node B (eNodeB). 
     In one embodiment, core IP network  110  comprises, at a minimum, devices which are capable of routing and forwarding IP packets between different hosts over the network. However, in one embodiment, the components of core IP network  110  may have additional functions, e.g., for functioning as a public land mobile network (PLMN)-General Packet Radio Service (GPRS) core network, for providing Voice over Internet Protocol (VoIP), Service over Internet Protocol (SoIP), and so forth, and/or may utilize various different technologies, e.g., Asynchronous Transfer Mode (ATM), Frame Relay, multi-protocol label switching (MPLS), and so forth. Thus, it should be noted that although core IP network  110  is described as an internet protocol network, this does not imply that the functions are limited to IP functions, or that the functions are limited to any particular network layer (e.g., the Internet layer). 
       FIG. 1  also illustrates a number of people at an event or gathering. For example, users  160 - 164  may be attendees at the event. As also illustrated in  FIG. 1 , a user  160  may take a photograph  190  of other attendees at the event using his/her endpoint device  170 . As shown, the photograph  190  may capture images of users  161 - 164  as participants. Notably, user  160  may then desire to share the photograph  190  with one or more of the participants in the photograph. If the user  160  is close friends with the participants to whom he or she desires to send the photograph, the user  160  may have no difficulty in sending the photograph as an MMS message or as an attachment to an email, since user  160  likely has contact information to send the photograph to these participants. However, if the gathering is very large, or if one or more of the participants are friends of friends that the user  160  may have only recently met, it is more difficult for user  160  to share the photograph with the other participants in the photograph. For example, user  160  may be close friends with and/or already have contact information for user  161 . On the other hand, user  160  may have met user  162  for only the first time at this event. Of course user  161  could simply ask user  162  for his or her phone number or email address and send the photograph to user  162  in the same manner as the photograph is sent to user  161 , e.g., in a conventional way. However, even where user  160  has previously obtained contact information of a participant, e.g., where the participant is a close friend, it is often time consuming to create a message for sending a photograph or other media content. It is even more time consuming when there are large numbers of participants with whom a user may desire to share a piece of captured media content. Although it is well known to send a single email to a large number of recipients and to send MMS messages to multiple destination telephone numbers, it still requires considerable effort to populate an addressee/recipient list and attach the media content. 
     In contrast, the present disclosure provides a novel way for users to automatically discover or identify participants in a media content and the share the media content with such identified participants. For example, one embodiment the present disclosure comprises identifying faces of one or more participants in a photograph using facial recognition techniques based upon stored biometric data of the one or more participants, and sending the photograph to one or more of the identified participants based upon contact information associated with the one or more identified participants. For example, in one embodiment, device  170  may have a contact list of various contacts of the user  160 . Each contact may have a profile that includes a name, phone number, email address, home and/or business address, birthday, a profile picture, and so forth. In addition, in one embodiment the profile for each contact in the contact list may also include biometric data regarding the contact. For example, in addition to a profile picture, the profile may include one or more photographs of the contact, videos of the contact, voice recordings of the contact and/or metadata regarding the image, voice, dress, gait and/or mannerisms of the contact that are derived from similar sources. In one embodiment, the contact list with biometric data is initially populated from previous photographs, audio recordings, video recordings, and so forth, which capture or depict contacts/friends of the user. Alternatively, or in addition, the contact list may be created from biometric data and contact information of users who are direct/first degree friends/contacts with the user on a social network. For example, the user and a contact may be first degree contacts where one of the user and the contact has indicated to the social network that he or she should be associated with the other. In one embodiment, the user and a contact are first degree contacts where each, i.e., both the user and the contact, have indicated to the social network a desire to be associated with the other. 
     In one embodiment, with the benefit of biometric data regarding the contacts of the user  160  stored on endpoint device  170 , the endpoint device  170  can match participants in the photograph  190  with contacts in the contact list on endpoint device  170 . For example, if users  163  and  164  are in the contact list on endpoint device  170 , the endpoint device  170  may automatically identify the faces of users  163  and  164  in photograph  190  based upon a facial recognition matching algorithm that matches a set of one or more known images of the faces of users  163  and  164 , e.g., from biometric data stored in profiles in the contact list, with faces detected in the photograph  190 . Once users  163  and  164  are identified as participants in the photograph  190 , endpoint device  170  may automatically send the photograph  190  to the identified users. For example, endpoint device  170  may utilize one or more contact methods to send the photograph  190  to the identified participants depending upon the preferences of the identified participants and the availability of one or more contact methods. For example, endpoint device  170  may have only an email address for user  163 , but may have both a phone number and an email address for user  164 . Thus, in one embodiment endpoint device  170  may send the photograph  190  to user  164  using both email and a MMS message if the phone number is for a cellular phone. 
     Returning to the present example, the endpoint device  170  may be capable or recognizing users  163  and  164  in photograph  190  based upon biometric data stored on the device, since users  163  and  164  are already in the contact list of user  160 . However, user  162  also appears in the photograph  190 , but may not be a previous contact of user  160 . Thus, endpoint device  170  may detect a face of user  162  in the photograph  190 , but is not able to recognize or match the face to any known person. 
     To address this issue, the present disclosure provides several solutions. In one example, endpoint device  170  may poll other nearby/proximate devices to solicit biometric data regarding owners of the devices. For example, if two endpoint devices are within range to communicate using near-field communication techniques such as Bluetooth, ZigBee, Wi-Fi, and so forth, or are in communication with a same cellular base station the endpoint devices may be deemed proximate to one another. In one example, endpoint device  170  may solicit from endpoint device  172  biometric data regarding the device owner (i.e., user  162 ), that can then be used by device  170  to match the unknown face to user  162 . Thereafter, having matched the unknown face in photograph  190  to user  162 , endpoint device  170  can send photograph  190  to endpoint device  172  in order that user  162  can have a copy. In addition, endpoint device  170  may store for future use an image of user  162  from the photograph  190  along with the contact information and/or further biometric data for user  162  which it receives from device  172 . 
     In another example, endpoint device  170  can poll the devices of other participants who have already been identified in the photograph  190  to provide biometric data on the contacts in the respective contact lists of such other participants. Thus, if user  162  is a second degree contact (e.g., a friend of a friend of user  160 ) endpoint device  170  may obtain biometric data on user  162  in order to identify user  162  in the photograph  190 . In another example, endpoint device  170  may first send the photograph  190  to a device of an identified participant and request that the other device attempt to identify any still unknown participants. This may avoid the unnecessary transfer of biometric data between users or participants who are merely acquaintances and not close friends or direct contacts with one another, thus maintaining a greater degree of privacy for individuals who may implement the present disclosure. 
     As an example, endpoint device  170  may identify user  161  as a participant in the photograph  190  and may thereafter send the photograph  190  to endpoint device  171  of user  161 , requesting that endpoint device  171  attempt to identify any still unknown participants in the photograph  190 . Endpoint device  171  may have a contact list of user  161  stored thereon. In addition, user  161 &#39;s contact list may include an entry for user  162 , who is a friend/contact of user  161 . More specifically, the entry for user  161  may include contact information for user  162 , along with biometric data for user  162 . Accordingly, endpoint device  171  may use similar techniques to endpoint device  170  (e.g., facial recognition techniques) in an attempt to identify any still unknown participants in the photograph. In this example, endpoint device  171  may match an unknown face in photograph  190  to user  162 . In addition, having made the match, endpoint device  171  may return the contact information for user  161  to endpoint device  170 . 
     In one embodiment, endpoint device  171  may also send biometric data, or a contact profile that include the biometric data for user  161  along with the contact information (e.g., a profile photograph). In addition, in one embodiment the endpoint device  170  may create a new profile or store a received contact profile for user  161 . For instance, the endpoint device  170  may store an image of user  162  from the photograph  190  along with the contact information and/or further biometric data for user  162  which it receives from endpoint device  171 . Thereafter, endpoint device  170  may forward the photograph  190  to a device of user  162  using the contact information that it obtains from endpoint device  171 . For example, endpoint device  170  may send the photograph  190  to endpoint device  172 , or another device associated with user  162  (e.g., an email server) using a cellular telephone number, Bluetooth device name, email address, social networking username, and so forth. 
     In another example, the user  160  may desire to share the photograph  190  with the other participants captured in photograph  190 , but may not wish to divulge his/her personal contact information. Similarly, the unknown participants in the photograph  190  may wish to receive an electronic copy of the photograph, but are wary to share their phone numbers or other contact information. Thus, in one embodiment, endpoint device  170  may also request or instruct a device of a known participant (e.g., endpoint device  171 ) to forward the photograph  190  to any of the unknown participants that it can identify. Thus, in this example, there is no direct communication from the endpoint device  170  of user  160  to the device  172  of the unknown participant (user  162 ). 
     In still another example, endpoint device  170  may solicit biometric data from a social network in an effort to identify an unknown participant. For example, social network  130  may store biometric data regarding members of the social network in its member profiles. In this example, users  160 - 164  may all be members of a social network. Users  161 ,  163  and  164  may be contacts or friends of user  160  within the social network  130 . However, user  162  may only be a contact/friend with user  161 . Device  170  may thus query the social network  130  for biometric data/profile information regarding members of the social network. For example, social network  130  may store, e.g., in database (DB)  128  of application server  127  member profiles that include biometric data, such as profile photographs, voice recordings, video recordings, and the like for a number of members of the social network. In one embodiment, social network  130  provides biometric data regarding only first degree and second degree contacts/friends of user  160  in an effort to identify participants in the photograph  190 . In one embodiment, the social network  130  only provides biometric data of a second degree contact of the user  160  who also is a first degree contact of a known participant that has already been identified in the photograph  190  (e.g., user  161 ). 
     It should be noted that in one example, biometric data from social network  130  is used to pre-populate a contact list on endpoint device  170  with profiles that include contact information and/or biometric data for friends/contacts of user  160 , and/or is used to supplement information that is contained in the contact list profiles on device  170 . However, in another embodiment, biometric data from social network  130  is the primary or only source of information that is used for identifying participants in photograph  190 . For example, device  170  may not have any useful biometric data stored thereon. Rather, it may access the social network  130  to obtain biometric data on friends/contacts of the user  160  at every instance when it needs to identify participants in a photograph or other media content. Thus, in this example endpoint device  170  may identify participants in photograph  190  only to the extent that it is able to obtain from social network  130  biometric data regarding the participants. In any case, endpoint device  170  may be successful in obtaining biometric data and contact information regarding user  162  from social network  130  (e.g., from social network member profiles stored in DB  128  of AS  127 ) such that device  170  is able to match user  162  to the previously unidentified participant in photograph  190 . Accordingly, endpoint device  170  may send the photograph  190  to user  162  using the contact information for user  162 , e.g., by sending the photograph as a MMS message to a cellular telephone number for endpoint device  172  (which is the device of user  162 ). 
     Similarly, although the foregoing examples describe a process that is performed by or on endpoint device  170 , another embodiment the present disclosure is implemented on a network-based application server, e.g., one of application servers  120 ,  125  or  127 . For example, photograph  190  may be captured on endpoint device  170  of user  160  and uploaded to application server (AS)  127  of social network  130 . Thereafter, AS  127  may use facial recognition techniques to identify participants in photograph  190  based upon biometric data stored in database (DB)  128  in connection with social network user profiles, e.g., of first and/or second degree contacts/friends of user  160 . Once one or more of the participants are thus identified, the AS  127  may then send the photograph  190  to the identified participants. A different embodiment may instead involve AS  125  and DB  126  storing biometric data and/or user contact information, where the AS  125  is operated by a third-party that is different from the operator of core IP network  110  and different from the operator of social network  130 . The AS  125  may provide biometric data and contact information in response to a query from an endpoint device, or may itself perform operations to identify known and unknown participants in a photograph or other captured media and to disseminate the captured media to any participants who are ultimately identified. 
     Similarly, the present disclosure may be implemented by AS  120  and DB  121  storing biometric data and/or user contact information, e.g., operated by a telecommunications network service provider that may own and/or operate core IP network  110  and/or cellular access network  140 . For instance, device  170  may upload photograph  190  to AS  120  for identifying participants, determining one or more methods to send the photograph to participants who are identified, and sending the photograph accordingly. In one example, AS  120  may maintain profile information in DB  121 , which may include biometric data on network subscribers (where one or more of users  160 - 164  are network subscribers). In another example, AS  120  may access biometric data from social network profiles of a user&#39;s contacts/friends from social network  130 . Similarly, in one embodiment one or more subscribers, e.g., user  160 , may maintain a network-based contact list, e.g., in DB  121  of AS  120 , instead of or in addition to a contact list stored on the user  160 &#39;s endpoint device  170 . 
     It should be noted that although the above examples describe identifying participants in a photograph using facial recognition techniques, the present disclosure is not so limited. For example, the present disclosure may substitute for or supplement facial recognition techniques by identifying a body shape of a participant and/or by identifying articles of clothing, e.g., where there is access to prior photographs from a same day and where a participant may be wearing the same distinctive outfit. In addition, the above examples are described in connection with sharing of a photograph  190 . However, the present disclosure is not limited to any particular media content type, but rather encompasses various forms of media content, e.g., photographs, audio recordings and video recordings (with or without accompanying audio). Thus, in another embodiment the present disclosure is for sharing an audio recording. In such case, the biometric data that is used may comprise a voice recording of a user or participant&#39;s voice. Thus, biometric data stored in a contact profile in a contact list on endpoint device  170  or  171 , stored in DB  121  of AS  120 , stored in DB  126  of AS  126  and/or stored in DB  128  of AS  127  may include one or more of such voice recordings for a user or participant. For example, although a single prior voice recording may be sufficient to match a voice in a captured audio recording, a more accurate or more confident matching may be achievable where there are multiple prior voice recordings or longer prior voice recordings of a particular participant. Similarly, in still another embodiment the present disclosure is for sharing video recordings (which may or may not include an audio component). In such an embodiment, the present disclosure may, for example, identify a participant using a combination of facial recognition techniques and voice matching techniques. In addition, in such a case the useful biometric data may also include gait and/or mannerisms of a participant that are derived from one or more previous video recordings. Thus, the present disclosure may employ any one or a combination of the above types of biometric data in an effort to identify a participant in a captured video. 
     In one embodiment, the present disclosure may automatically transfer photograph  190  or other captured media content to other participants that are identified. For example, as mentioned above, user  160  may take photograph  190  using endpoint device  170 . Endpoint device  170  (or one of the network-based application servers  120 ,  125  or  127 ) may then identify users  161 - 164  using any one or more the techniques described above, e.g., using biometric data from a contact list on endpoint device  170 , using biometric data from a contact list on endpoint device  171  of user  161 , using biometric data obtained from social network  130 , and so forth. Once users  161 - 164  are identified, endpoint device  170  (or one of the network-based application servers  120 ,  125  or  127 ) may then automatically send an email to known email addresses of users  163  and  164 . 
     For example, the email addresses may be stored as part of the contact profile information for the attendees wherever the profile information is stored, e.g., locally on device  170 , in DB  121 , DB  126 , DB  128 , in social network  130 , etc. Similarly, an MMS message may automatically be sent to cellular telephone numbers associated with devices of users  161  and  162 . Thus, different communication channels may be used to send the photograph  190  to different participants that are identified. As still another example, assume that in the first instance only user  161  is identified in photograph  190 . Accordingly, endpoint device  170  (or one of the network-based application servers  120 ,  125  or  127 ) may request that device  171  of user  161  to automatically send the photograph  190  to devices of any unknown participants that the endpoint device  171  is itself able to identify. It should be noted that the present disclosure is not limited to any particular contact method for sending a photograph or other media content. Thus, the present disclosure may send media content to the identified participants using usernames or other identifiers, e.g., messaging service usernames, social network usernames, IP addresses, Bluetooth device identifiers, and so forth. 
     In another embodiment, the present disclosure may prompt the user  160  before sending the photograph  190 . For instance, endpoint device  170  may present a list or use other means to indicate which participants/users have been identified in the photograph  190 , and may include prompts to the user  160  to select the identified participants to which it should send the photograph  190 . In addition, the same or similar operations may be followed by a network-based implementation of the present disclosure. For example, endpoint device  170  may maintain a session for user  160  with AS  120 . Thus, when AS  120  identifies all participants in the photograph  190  that it is able to identify, AS  120  may prompt the user  160  to select the users/identified participants to which to send the photograph  190 . 
       FIG. 2  illustrates a flowchart of a method  200  for forwarding a media content. In one embodiment, steps, functions and/or operations of the method  200  may be performed by an endpoint device, such as endpoint device  170  in  FIG. 1 , or by a network-based device, e.g., application server  120 ,  125  or  127  in  FIG. 1 . In one embodiment, the steps, functions, or operations of method  200  may be performed by a computing device or system  500 , and/or processor  502  as described in connection with  FIG. 5  below. The method begins in step  205  and proceeds to optional step  210 . 
     At optional step  210 , the method  200  captures a media content. For example, the method  200  may capture a photograph, audio recording or video at step  210  using a camera and/or microphone of a smartphone, a digital camera or other multimedia device. In one embodiment, the media content may include a number of participants that are to be identified. In one embodiment, optional step  210  is performed when the method  200  is implemented at an endpoint device, such as endpoint device  170  in  FIG. 1 . 
     At optional step  220 , the method  200  receives the captured media content. For example, the method  200  may receive from a smartphone, digital camera or other multimedia device the media content that is captured at step  210 . For example, a user who has captured the media content using his/her personal endpoint device may upload the media content to a network-based device to perform identification of participants, to contact the participants and to provide the participants with their own electronic copies of the media content. In one embodiment, optional step  220  is performed as part of the method  200  when implemented by a network-based device such as application server  120 ,  125  or  127  in  FIG. 1 . 
     At step  230 , the method  200  identifies a known participant in the media content. For example, a photograph that is taken by a user may include the likeness of a friend of the user and who is on a contact list of the user, or who is connected to the user on a social network. Accordingly, at step  230 , the method  200  may access biometric data regarding contacts and/or friends of the user who has captured or uploaded the media content. For instance, step  230  may involve accessing a contact list stored on an endpoint device of the user, or stored on a network-based device executing the method  200 . The contact list may include a profile having biometric data and contact information for the known participant. In one embodiment, the contact list with biometric data is initially populated from previous photographs, audio recordings, video recordings, and so forth, which capture or depict contacts/friends of the user. Alternatively, or in addition, the contact list may be created from biometric data and contact information of users who are direct/first degree friends/contacts with the user on a social network. 
     Alternatively, or in addition, step  230  may involve accessing social network profile information from a server of a social network, where the profile information includes biometric data that is useable to identify a participant in the media. In any case, at step  230 , the method  200  may compare all or a portion of the media content, e.g., faces, body shapes, clothing, voice identifiers, gaits, mannerisms and so forth from the media content with similar types of biometric data that is obtained for the known contacts/friends of the user. When a match between a contact/friend of the user and a participant in the media content is obtained, the method  200  may note the match. In addition, in one embodiment at step  230 , the method  200  may automatically send the media content to the known participant(s) who are identified, or may prompt the user whether he or she would like to send the media content to any identified participant(s). For example, the method  200  may send the media content to the devices of any known and identified participants using contact details such as cellular telephone numbers, email addresses, internet protocol (IP) addresses, social network and/or messaging application usernames, and so forth. In one embodiment, the method  200  may send the media content using near-field communication techniques, e.g., Wi-Fi/peer-to-peer, Bluetooth, and the like, or may send the media content as an attachment to an email, a MMS message, a social networking message, and so forth. 
     At step  240 , the method  200  detects an unknown participant in the media content. For example, the method  200  may identify that there are four participants who appear in the media content, e.g., a photograph or video. In addition, at step  230 , the method  200  may previously identify three of the four participants by matching likenesses of the three participants to their biometric data obtained at step  230 , e.g., derived from a contact list, database and/or social network profile information. However, while the method  200  may have detected that there are four different participants, it is unable to presently identify one of the participants. For example, the unknown participant may not be a friend/or contact of the user, e.g., the unknown participant is not in a contact list of the user and/or is not a first degree friend/contact of the user in a social network. 
     In step  250 , the method  200  sends a request to a device of one of the known participants requesting the device to identify any unknown participants and to provide contact information for the unknown participants that it is able to identify. For example, the method  200  may have previously sent the media content to the device of the known participant at step  230 , or may send the media content at step  250  as part of the request. In one embodiment, the method  200  sends only a portion of the media content in connection with the request. For example, the method  200  may send only a portion, or portions of a picture that include an unidentified face, or may send only an audio clip that includes an unidentifiable voice, for instance. In one embodiment, step  250  comprises sending a request to one, several or all devices of known participants who have previously been identified in the media content. 
     In one embodiment, the device of a known participant that receives the request may be a portable endpoint device, e.g., a smartphone, a tablet computer or the like. However, in another embodiment the device that receives the request may comprises a home computer, a desktop computer, or even a server of a communications network provider or social network. Thus, a device of a known participant to which the request is sent may broadly comprise any device that is associated with the known participant and which is capable of attempting to identify an unknown participant. In one embodiment, the receiving device to which the request is sent is determined using the same set of contact information from which the method  200  obtains the biometric data used to identify the known participant. 
     Regardless of the specific device that receives the request or the manner in which the request is sent, the receiving device may then perform similar operations to those performed at step  230 . Namely, the receiving device may consult with a contact list stored on the receiving device, or may obtain contact information from a network-based device (e.g., a database of a communication network provider, of a social network provider or of a third-party). More specifically, the receiving device, in one embodiment may have access to biometric data for all contacts/friends of the known participant who is associated with the receiving device. Accordingly, the pool of potential matches for the unknown participant detected at step  240  is significantly increased to include all of the friends/contacts of the known participant that are accessible to the receiving device (the device that receives the request sent at step  250 ). For instance, the unknown participant may be identified using biometric data of the unknown participant contained on the device of the known participant. 
     In step  260 , the method  200  receives from the device of the known participant contact information for the unknown participant, e.g., when the unknown participant is identified. Thus the receipt of the contact information may also serve as a positive acknowledgement that an unknown participant has been identified. For instance, the device of the known participant that receives the request sent at step  250  may successfully identify one or more unknown participants in a photograph, audio recording or video using accessible biometric data from a contact list stored on the device or accessible to the device from a network-based source (e.g., from a database/application server, a social network, and so forth). In addition, the device may obtain contact information from the same source(s) as the biometric data, e.g., from a profile entry in a contact list, where the profile entry includes biometric data as well as contact information for the unknown participant. The contact information may include one or more ways to communicate with the unknown participant, e.g., a cellular telephone number, an email address, a messaging application username, an IP address, a Bluetooth device name, and the like. As such, when there is a positive match to one of the unknown participants, the device may reply that it has made a positive identification, along with one or more types of contact information for the unknown participant, which is received by the method  200  at step  250 . 
     In one embodiment, step  260  comprises only receiving contact information for the unknown participant. However, in another embodiment the method  200  may additionally receive biometric data for the unknown participant at step  260 . For example, the device that identifies the unknown participant and sends the contact information may also include biometric data for the unknown participant in the response. Thus, at step  260  the method  200  may additionally store the contact information along with biometric data for the unknown participant who is identified. Consequently, when encountering an image, likeness or voice of the unknown participant in any subsequent media content, the method  200  may directly identify the unknown participant without having to resort to querying other devices. 
     At step  270 , the method  200  sends the media content to a device of the unknown participant using the contact information received at step  260 . For instance, as mentioned above, at step  260  the method  200  may obtain contact information as a positive acknowledgement that an unknown participant has been identified. Accordingly, at step  270  the method  200  may send the media content to the device of the unknown participant based upon the contact information received at step  260 . It should be noted that step  270  broadly comprises sending the media content to a device of the unknown participant. However, the method  200  may not necessarily be aware of, or have access to the identity of the specific device of the unknown participant that will ultimately receive the media content. For example, if the media content is sent to an email address, the unknown participant may immediately receive the email at a smartphone while still in the presence of the user who captured the media content. However, it is equally plausible that the unknown participant may access the email at a later time, e.g., via a home computer or a work computer. Thus, the device of the unknown participant to which the media content is sent at step  270  broadly comprises any device that is associated with the unknown participant and that is capable of receiving the media content on behalf of the unknown participant, including a smartphone, personal computer, an email server, a server or other device operated by a social network provider, and so forth. 
     Following step  270 , the method  200  proceeds to step  295  where the method ends. 
       FIG. 3  illustrates a flowchart of method  300  for forwarding a media content. In one embodiment, steps, functions and/or operations of the method  300  may be performed by an endpoint device, such as endpoint device  170  in  FIG. 1 . In one embodiment, the steps, functions, or operations of method  300  may be performed by a computing device or system  500 , and/or processor  502  as described in connection with  FIG. 5  below. For illustrative purpose, the method  300  is described in greater detail below in connection with an embodiment performed by a processor, such as processor  502 . The method begins in step  305  and proceeds to optional step  310 . 
     At optional step  310 , the processor captures a media content. For example, the processor may capture a photograph, audio recording or video at step  310  using a camera and/or microphone of a smartphone, a digital camera or other multimedia device. In one embodiment, the media content may include a number of participants that are to be identified. 
     At optional step  320 , the processor receives the captured media content. For example, the processor may receive the media content from a secure digital (SD) card, from a memory stick or via an email, or may retrieve the captured media content from a local or attached memory, from storage on a server, and so forth. 
     At step  330 , the processor identifies a known participant in the media content. For example, a photograph that is taken by a user may include the likeness of a friend of the user and who is on a contact list of the user, or who is connected to the user on a social network. Accordingly, at step  330 , the processor may access biometric data regarding contacts and/or friends of the user who has captured or uploaded the media content. For instance, step  330  may involve accessing a contact list stored on an endpoint device that includes the processor. The contact list may include a profile having biometric data and contact information for the known participant. Notably, step  330  may involve the same or similar functions/operations described in connection with step  230  of the method  200  above. 
     At step  340 , the processor detects an unknown participant in the media content. For example, the processor may identify that there are four participants who appear in the media content, e.g., a photograph or video. In addition, at step  330 , the processor may previously identify three of the four participants by matching likenesses of the three participants to their biometric data obtained at step  230 , e.g., derived from a contact list, database and/or social network profile information. However, while the processor may have detected that there are four different participants, it is unable to presently identify one of the participants. For example, the unknown participant may not be a friend/or contact of the user, e.g., the unknown participant is not in a contact list of the user and/or is not a first degree friend/contact of the user in a social network. Notably, step  340  may involve the same or similar functions/operations described in connection with step  240  of the method  200  above. 
     In step  350 , the processor obtains wirelessly, from a device of the known participant that is proximate to the processor, biometric data and contact information for a plurality of contacts that include the unknown participant. In one embodiment, step  350  comprises obtaining biometric data and contact information from several or all devices of known participants who have previously been identified in the media content. In one embodiment, the processor sends a request wirelessly to a mobile device of a known participant that is proximate to the processor. In one embodiment, the receiving device to which the request is sent is identified using the same set of contact information from which the method  300  obtains the biometric data used to identify the known participant. In one embodiment, the request is sent using near-field communication techniques such as Bluetooth, ZigBee, Wi-Fi, and so forth. In another embodiment, a request is sent using a MMS message over a cellular network, an email, or other technique. However, in one example, regardless of the manner in which a request is sent, it will only be sent to a device of a known participant or a device of a contact/friend of the user which is proximate to the processor (e.g., proximate to another mobile device that includes the processor). In one embodiment, the processor only contacts devices of known participants that are proximate to the processor. However, in a different embodiment the processor may contact a device of any friend/contact if the friend/contact&#39;s device is proximate to the processor. This may be useful where, for example, a friend of a friend appears in a photograph but where the friend-in-common who is present at the event just so happens to not be in that particular photograph. 
     In one embodiment, two devices are deemed proximate to one another where each device is serviced by a same cellular base station or wireless (e.g., Wi-Fi) access point. In another embodiment, two devices are deemed proximate where the devices are in range to communicate using a near-field communication method. In another embodiment, two devices are deemed proximate when the devices are within a certain distance of one another as determined by cellular triangulation techniques, or as determined using global positioning system (GPS) information obtained from each device. 
     The receiving device may retrieve biometric data and contact information for all or a portion of the contacts/friends of the known participant who is associated with the receiving device. In addition, the receiving device may then return such information to the processor. Accordingly, at step  350 , the processor may receive wirelessly from the device of the known participant a contact list, or a portion of the entries in a contact list which include biometric data and contact information for a plurality of contacts of the known participant. Notably, in one embodiment the biometric data and contact information for the unknown participant is included therewith. 
     At step  360 , the processor identifies the unknown participant in the media content using the biometric data that is obtained wirelessly. For example, the processor may attempt to match biometric data from one or more of the contacts received at step  350  with a portion of the media content that captures the unknown participant. In one embodiment, the processor accesses each entry in a contact list received at step  350 , accesses the biometric data, and compares it to a portion of the captured media until a positive match is found. In this way, the pool of potential matches for the unknown participant detected at step  340  is significantly increased to include all of the friends/contacts of the known participant, which are now accessible to the processor. 
     At step  370 , the method  300  sends the media content to a device of the unknown participant using the contact information received at step  350 . For example, the contact information received at step  350  may include one or more ways to communicate with the unknown participant, e.g., a cellular telephone number, an email address, a messaging application username, an IP address, a Bluetooth device name, and the like. It should be noted that step  370  broadly comprises sending the media content to a device of the unknown participant. 
     At optional step  380 , the processor stores the biometric data and contact information of the unknown participant, e.g., on a local memory attached to or included in a device that comprises the processor. Consequently, when encountering an image, likeness or voice of the unknown participant in any subsequent media content, the processor may directly identify the unknown participant without having to resort to querying other devices. 
     At optional step  390 , the processor identifies the unknown participant in a subsequent media content using the biometric data that is stored at optional step  380 . Advantageously, the processor need not query other devices in order to identify the unknown participant in further media contents that are captured or received. For example, participants at an event may take many photographs which they would like to share. Thus, even if two of the participants are not previously associated with one another, it would be beneficial that the processor need not query external devices for each and every new photograph. 
     Following step  370 , or following optional step  390 , the method  300  proceeds to step  395  where the method ends. 
       FIG. 4  illustrates a flowchart of still another method  400  for forwarding a media content. In one embodiment, steps, functions and/or operations of the method  400  may be performed by an endpoint device, such as endpoint device  170  in  FIG. 1 , or by a network-based device, e.g., application server  120 ,  125  or  127  in  FIG. 1 . In one embodiment, the steps, functions, or operations of method  400  may be performed by a computing device or system  500 , and/or processor  502  as described in connection with  FIG. 5  below. The method begins in step  405  and proceeds to optional step  410 . 
     At optional step  410 , the method  400  captures a media content. For example, the method  400  may capture a photograph, audio recording or video at step  410  using a camera and/or microphone of a smartphone, a digital camera or other multimedia device. In one embodiment, the media content may include a number of participants that are to be identified. In one embodiment, optional step  410  is performed when the method  400  is implemented at an endpoint device, such as endpoint device  170  in  FIG. 1 . 
     At optional step  420 , the method  400  receives the captured media content. For example, the method  400  may receive from a smartphone, digital camera or other multimedia device the media content that is captured at step  410 . For example, a user who has captured the media content using his/her personal endpoint device may upload the media content to a network-based device to perform identification of participants, to contact the participants and to provide the participants with their own electronic copies of the media content. In one embodiment, optional step  420  is performed as part of the method  400  when implemented by a network-based device such as application server  120 ,  125  or  127  in  FIG. 1 . 
     At step  430 , the method  400  identifies a known participant in the media content. For example, a photograph that is taken by a user may include the likeness of a friend of the user and who is on a contact list of the user, or who is connected to the user on a social network. Accordingly, at step  430 , the method  400  may access biometric data regarding contacts and/or friends of the user who has captured or uploaded the media content. For instance, step  430  may involve accessing a contact list stored on a device executing the method  400 . The contact list may include a profile having biometric data and contact information for the known participant. Notably, step  430  may involve the same or similar functions/operations described in connection with steps  230  or  330  of the respective methods  200  and  300  above. 
     At step  440 , the method  400  detects an unknown participant in the media content. For example, the method  400  may identify that there are four participants who appear in the media content. In addition, at step  430 , the method  400  may previously identify three of the four participants by matching likenesses of the three participants to their biometric data obtained at step  430 , e.g., derived from a contact list or profile information stored on a device executing the method  400  or obtained from a network-based server and/or database. However, while the method  400  may have detected that there are four different participants, it is unable to presently identify one of the participants. Notably, step  440  may involve the same or similar functions/operations described in connection with steps  240  and  340  of the respective methods  200  and  300  above. 
     In step  450 , the method  400  obtains from a server of a social network, biometric data and contact information for a plurality of contacts that include the unknown participant. Notably, in one embodiment the server of the social network only provides biometric data and contact information of contacts/friends who are first and second degree contacts of the user. In addition, in one embodiment the server only provides biometric data of a second degree contact of the user who also is a first degree contact of a known participant that has already been identified in the media content. In one embodiment, the method  400  sends a request to the server of the social network seeking available biometric data and contact information for a plurality of contacts, where the request includes the identity of the known participant who is identified in the media content at step  430 . The server of the social network may reply with a list of friends/contacts of the known participant. In one embodiment, the server may provide one or more profiles/entries for the respective friends/contacts of the known participant, where each profile includes biometric data and contact information for one of the friends/contacts. Notably, in one embodiment the biometric data and contact information for the unknown participant is included therewith. 
     At step  460 , the method  400  identifies the unknown participant in the media content using the biometric data that is obtained from the server of the social network. For example, the method  400  may attempt to match biometric data from one or more of the contacts received at step  450  with a portion of the media content that captures the unknown participant. In one embodiment, the method  400  accesses each entry or profile in a list of contacts/friends received at step  450 , accesses the biometric data, and compares it to a portion of the captured media until a positive match is found. In this way, the pool of potential matches for the unknown participant detected at step  440  is significantly increased to include all of the friends/contacts of the known participant from a social network, which are now accessible to the method  400 . 
     At step  470 , the method  400  sends the media content to a device of the unknown participant using the contact information received at step  450 . For example, the social network profile of the unknown participant that is received at step  450  may include contact information that provides one or more ways to communicate with the unknown participant, e.g., a cellular telephone number, an email address, a messaging application username, an IP address, a Bluetooth device name, and the like. 
     At optional step  480 , the method  400  stores the biometric data and contact information of the unknown participant, e.g., on a local memory attached to or included in a device that comprises the processor. Consequently, when encountering an image, likeness or voice of the unknown participant in any subsequent media content, the method  400  may directly identify the unknown participant without having to resort to querying other devices. 
     At optional step  490 , the method  400  identifies the unknown participant in a subsequent media content using the biometric data that is stored at optional step  480 . Advantageously, the method  400  need not query other devices (e.g., a server of a social network) in order to identify the unknown participant in further media contents that are captured or received. For example, participants at an event may take many photographs which they would like to share. Thus, even if two of the participants are not previously associated with one another, it would be beneficial that the method  400  need not query external devices, such as a social network server, for each and every new photograph. 
     Following step  470 , or following optional step  490 , the method  400  proceeds to step  495  where the method ends. 
     It should be noted that although not specifically specified, one or more steps, functions or operations of the respective methods  200 ,  300  and/or  400  may include a storing, displaying and/or outputting step as required for a particular application. In other words, any data, records, fields, and/or intermediate results discussed in the respective methods can be stored, displayed and/or outputted to another device as required for a particular application. Furthermore, steps or blocks in  FIGS. 2-4  that recite a determining operation or involve a decision do not necessarily require that both branches of the determining operation be practiced. In other words, one of the branches of the determining operation can be deemed as an optional step. 
       FIG. 5  depicts a high-level block diagram of a general-purpose computer or system suitable for use in performing the functions described herein. For example, any one or more components or devices illustrated in  FIG. 1  or described in connection with the methods  200 ,  300  or  400  may be implemented as the system  500 . As depicted in  FIG. 5 , the system  500  comprises a hardware processor element  502  (e.g., a microprocessor, a central processing unit (CPU) and the like), a memory  504 , (e.g., random access memory (RAM), read only memory (ROM), a disk drive, an optical drive, a magnetic drive, and/or a Universal Serial Bus (USB) drive), a module  505  for forwarding a media content, and various input/output devices  506 , e.g., a camera, a video camera, storage devices, including but not limited to, a tape drive, a floppy drive, a hard disk drive or a compact disk drive, a receiver, a transmitter, a speaker, a display, a speech synthesizer, an output port, and a user input device (such as a keyboard, a keypad, a mouse, and the like). 
     It should be noted that the present disclosure can be implemented in software and/or in a combination of software and hardware, e.g., using application specific integrated circuits (ASIC), a general purpose computer or any other hardware equivalents, e.g., computer readable instructions pertaining to the method(s) discussed above can be used to configure a hardware processor to perform the steps functions and/or operations of the above disclosed methods. In one embodiment, the present module or process  505  for forwarding a media content can be implemented as computer-executable instructions (e.g., a software program comprising computer-executable instructions) and loaded into memory  504  and executed by hardware processor  602  to implement the functions as discussed above. As such, the present module or process  505  for forwarding a media content as discussed above in methods  200 ,  300  and  400  (including associated data structures) of the present disclosure can be stored on a non-transitory (e.g., tangible or physical) computer readable storage medium, e.g., RAM memory, magnetic or optical drive or diskette and the like. 
     While various embodiments have been described above, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of a preferred embodiment should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.