OBTAINING ARTIST IMAGERY FROM VIDEO CONTENT USING FACIAL RECOGNITION

1 . A tangible, non-transitory computer readable medium comprising instructions that, when executed, cause at least one processor to perform a set of operations comprising:

receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program;

applying an automated face recognition program implemented on a computing device to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, wherein each of at least a subset of the prior-determined set of feature vectors is associated with a respective one of the particular people; and

storing, in non-transitory computer-readable memory, the digital image together with information (i) assigning respective identities of the recognized one or more of the particular people in the digital image, and (ii) associating with each respective assigned identity geometric coordinates in the digital image of a face to which the identity is assigned.

2 . The tangible, non-transitory computer readable medium of claim 1 , wherein applying the automated face recognition program implemented to the digital image to recognize, based on the at least one feature vector from the prior-determined set of feature vectors, the one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, comprises:

determining a particular feature vector corresponding to at least one of the one or more faces detected in the digital image; and

determining that the at least one feature vector from the prior-determined set of feature vectors matches the particular feature vector with a probability that both exceeds a threshold and is greater than probabilities of any other feature vectors from the prior-determined set of feature vectors matching the particular feature vector.

3 . The tangible, non-transitory computer readable medium of claim 2 , wherein determining the particular feature vector corresponding to at least one of the one or more faces detected in the digital image comprises:

applying a face detection program to the digital image to detect a spatial region of the digital image that includes the at least one of the one or more faces detected, together with respective geometric coordinates of the spatial region; and

applying a computer-implemented feature extraction program to the spatial region of the digital image to generate the particular feature vector.

4 . The tangible, non-transitory computer readable medium of claim 1 , wherein at least one of the one or more of the particular people in the digital image is a cast member of the particular media content program.

5 . The tangible, non-transitory computer readable medium of claim 1 , wherein the particular media content program is one of: a television program, a movie, a sporting event, or a web-based user-hosted and/or user-generated content program.

6 . The tangible, non-transitory computer readable medium of claim 1 , wherein the set of operations further comprise:

receiving a further digital image associated with a further particular media content program, the further digital image containing one or more faces of further particular people associated with the further particular media content program;

applying the automated face recognition program to the further digital image to recognize, based on at least one further feature vector from a further prior-determined set of feature vectors, one or more of the further particular people in the further digital image from among one or more further faces detected, together with respective geometric coordinates for each of the one or more further detected faces in the further digital image, wherein each of at least a further subset of the further prior-determined set of feature vectors is additionally associated with a respective one of the further particular people; and

storing, in non-transitory computer-readable memory, the further digital image together with information (i) assigning respective identities of the recognized one or more of the further particular people in the further digital image, and (ii) associating with each respective assigned identity geometric coordinates in the further digital image of a further face to which the identity is assigned.

7 . The tangible, non-transitory computer readable medium of claim 6 , wherein the further prior-determined set of feature vectors and the prior-determined set of feature vectors are at least partially overlapping sets.

8 . The tangible, non-transitory computer readable medium of claim 6 , wherein the further digital image is different from the digital image,

wherein the further particular media content program is one of: different from the particular media content program, or the same as the particular media content program,

and wherein at least one of the recognized further particular people is one of: different from any of the recognized particular people, or the same as one of the recognized particular people.

9 . The tangible, non-transitory computer readable medium of claim 1 , wherein the prior-determined set of feature vectors comprises feature vectors associated with facial images, including those of at least a subset of the particular people,

and wherein each of one or more given feature vectors of the prior-determined set of feature vectors was extracted from one or more training digital images, and is associated both with a different one of images a given person in the one or more training digital images, and with an identifier of the given person.

10 . A computer-implemented method comprising:

receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program;

applying an automated face recognition program implemented on a computing device to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, wherein each of at least a subset of the prior-determined set of feature vectors is associated with a respective one of the particular people; and

storing, in non-transitory computer-readable memory, the digital image together with information (i) assigning respective identities of the recognized one or more of the particular people in the digital image, and (ii) associating with each respective assigned identity geometric coordinates in the digital image of a face to which the identity is assigned.

11 . The computer-implemented method of claim 10 , wherein applying the automated face recognition program implemented to the digital image to recognize, based on the at least one feature vector from the prior-determined set of feature vectors, the one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, comprises:

determining a particular feature vector corresponding to at least one of the one or more faces detected in the digital image; and

determining that the at least one feature vector from the prior-determined set of feature vectors matches the particular feature vector with a probability that both exceeds a threshold and is greater than probabilities of any other feature vectors from the prior-determined set of feature vectors matching the particular feature vector.

12 . The computer-implemented method of claim 11 , wherein determining the particular feature vector corresponding to at least one of the one or more faces detected in the digital image comprises:

applying a face detection program to the digital image to detect a spatial region of the digital image that includes the at least one of the one or more faces detected, together with respective geometric coordinates of the spatial region; and

applying a computer-implemented feature extraction program to the spatial region of the digital image to generate the particular feature vector.

13 . The computer-implemented method of claim 10 , further comprising:

receiving a further digital image associated with a further particular media content program, the further digital image containing one or more faces of further particular people associated with the further particular media content program;

applying the automated face recognition program to the further digital image to recognize, based on at least one further feature vector from a further prior-determined set of feature vectors, one or more of the further particular people in the further digital image from among one or more further faces detected, together with respective geometric coordinates for each of the one or more further detected faces in the further digital image, wherein each of at least a further subset of the further prior-determined set of feature vectors is additionally associated with a respective one of the further particular people; and

storing, in non-transitory computer-readable memory, the further digital image together with information (i) assigning respective identities of the recognized one or more of the further particular people in the further digital image, and (ii) associating with each respective assigned identity geometric coordinates in the further digital image of a further face to which the identity is assigned.

14 . The computer-implemented method of claim 13 , wherein the further prior-determined set of feature vectors and the prior-determined set of feature vectors are at least partially overlapping sets.

15 . The computer-implemented method of claim 13 , wherein the further digital image is different from the digital image,

wherein the further particular media content program is one of: different from the particular media content program, or the same as the particular media content program,

and wherein at least one of the recognized further particular people is one of: different from any of the recognized particular people, or the same as one of the recognized particular people.

16 . The computer-implemented method of claim 10 , wherein the prior-determined set of feature vectors comprises feature vectors associated with facial images, including those of at least a subset of the particular people,

and wherein each of one or more given feature vectors of the prior-determined set of feature vectors was extracted from one or more training digital images, and is associated both with a different one of images a given person in the one or more training digital images, and with an identifier of the given person.

17 . A computing device comprising:

at least one processors; and

tangible, non-transitory computer readable medium comprising instructions that, when executed, cause the at least one processor to perform a set of operations comprising:

receiving, at a computing device, a digital image associated with a particular media content program, the digital image containing one or more faces of particular people associated with the particular media content program;

applying an automated face recognition program implemented on a computing device to the digital image to recognize, based on at least one feature vector from a prior-determined set of feature vectors, one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, wherein each of at least a subset of the prior-determined set of feature vectors is associated with a respective one of the particular people; and

storing, in non-transitory computer-readable memory, the digital image together with information (i) assigning respective identities of the recognized one or more of the particular people in the digital image, and (ii) associating with each respective assigned identity geometric coordinates in the digital image of a face to which the identity is assigned.

18 . The computing device of claim 17 , wherein applying the automated face recognition program implemented to the digital image to recognize, based on the at least one feature vector from the prior-determined set of feature vectors, the one or more of the particular people in the digital image from among one or more faces detected, together with respective geometric coordinates for each of the one or more detected faces in the digital image, comprises:

determining a particular feature vector corresponding to at least one of the one or more faces detected in the digital image; and

determining that the at least one feature vector from the prior-determined set of feature vectors matches the particular feature vector with a probability that both exceeds a threshold and is greater than probabilities of any other feature vectors from the prior-determined set of feature vectors matching the particular feature vector.

19 . The computing device of claim 18 , wherein determining the particular feature vector corresponding to at least one of the one or more faces detected in the digital image comprises:

applying a face detection program to the digital image to detect a spatial region of the digital image that includes the at least one of the one or more faces detected, together with respective geometric coordinates of the spatial region; and

applying a computer-implemented feature extraction program to the spatial region of the digital image to generate the particular feature vector.

20 . The computing device of claim 17 , wherein the prior-determined set of feature vectors comprises feature vectors associated with facial images, including those of at least a subset of the particular people,

and wherein each of one or more given feature vectors of the prior-determined set of feature vectors was extracted from one or more training digital images, and is associated both with a different one of images a given person in the one or more training digital images, and with an identifier of the given person.