1. A method comprising: by one or more computing devices, receiving one or more images associated with a primary user, wherein at least one of the one or more images includes one or more detected faces; by the one or more computing devices, for each of the one or more detected faces, selecting a set of one or more candidates, wherein the set of one or more candidates comprises: users of a social network wherein each of the users are associated with a computed measure of affinity of the primary user for each candidate through the social network that exceeds a first predetermined threshold; and users determined by the social network to be public figures, wherein the public figures are each users of the social network that do not have a computed measure of affinity of the primary user for each candidate through the social network that exceeds the first predetermined threshold; by the one or more computing devices, for each of the one or more detected faces, selecting a subset of one or more candidates from the set of candidates based on a facial recognition score calculating by a facial recognition comparison of each candidate to the detected face, wherein each of the candidates in the subset of candidates has a facial recognition score above a second predetermined threshold; by the one or more computing devices, for each of the detected faces, calculating a candidate score for each of the candidates, wherein the calculation is based on: the facial recognition score for the candidate; and the computed measure of affinity for the candidate; and by the one or more computing devices, for each of the one or more faces, selecting a winning candidate from the subset of candidates to identify the face based on the candidate scores for the face.
1. A method comprising: by one or more computing devices, receiving one or more images associated with a primary user, wherein at least one of the one or more images includes one or more detected faces; by the one or more computing devices, for each of the one or more detected faces, selecting a set of one or more candidates, wherein the set of one or more candidates comprises: users of a social network wherein each of the users are associated with a computed measure of affinity of the primary user for each candidate through the social network that exceeds a first predetermined threshold; and users determined by the social network to be public figures, wherein the public figures are each users of the social network that do not have a computed measure of affinity of the primary user for each candidate through the social network that exceeds the first predetermined threshold; by the one or more computing devices, for each of the one or more detected faces, selecting a subset of one or more candidates from the set of candidates based on a facial recognition score calculating by a facial recognition comparison of each candidate to the detected face, wherein each of the candidates in the subset of candidates has a facial recognition score above a second predetermined threshold; by the one or more computing devices, for each of the detected faces, calculating a candidate score for each of the candidates, wherein the calculation is based on: the facial recognition score for the candidate; and the computed measure of affinity for the candidate; and by the one or more computing devices, for each of the one or more faces, selecting a winning candidate from the subset of candidates to identify the face based on the candidate scores for the face. 15. The method of claim 1 , wherein determining the winning candidate comprises using a hidden Markov model.