Face identification in videos from mobile cameras

It is still challenging to recognize faces reliably in videos from mobile camera, although mature automatic face recognition technology for still images has been available for quite some time. Suppose we want to be alerted when suspects appear in the recording of a police BodyCam, even a good face matcher on still images would give many false alarms due to the uncontrolled conditions. This paper presents an approach to identify faces in videos from mobile cameras. A commercial face matcher FaceVACS is used to process the face recognition frame by frame. On a video of certain length, in order to suppress the false alarms, we propose to count the recognized identities and set thresholds to the counts, as well as to the matching scores for still-image face recognition. In this way, the facial information of a single subject over time is exploited without implementing face tracking, which is complicated and more difficult for low-quality unconstrained videos. For experiments, videos are recorded by two type of mobile cameras, which provide different video qualities. The results demonstrate the efficiency of our proposed approach.