TY - GEN
T1 - Dictionary-based face recognition from video
AU - Chen, Yi Chen
AU - Patel, Vishal M.
AU - Phillips, P. Jonathon
AU - Chellappa, Rama
PY - 2012
Y1 - 2012
N2 - The main challenge in recognizing faces in video is effectively exploiting the multiple frames of a face and the accompanying dynamic signature. One prominent method is based on extracting joint appearance and behavioral features. A second method models a person by temporal correlations of features in a video. Our approach introduces the concept of video-dictionaries for face recognition, which generalizes the work in sparse representation and dictionaries for faces in still images. Video-dictionaries are designed to implicitly encode temporal, pose, and illumination information. We demonstrate our method on the Face and Ocular Challenge Series (FOCS) Video Challenge, which consists of unconstrained video sequences. We show that our method is efficient and performs significantly better than many competitive video-based face recognition algorithms.
AB - The main challenge in recognizing faces in video is effectively exploiting the multiple frames of a face and the accompanying dynamic signature. One prominent method is based on extracting joint appearance and behavioral features. A second method models a person by temporal correlations of features in a video. Our approach introduces the concept of video-dictionaries for face recognition, which generalizes the work in sparse representation and dictionaries for faces in still images. Video-dictionaries are designed to implicitly encode temporal, pose, and illumination information. We demonstrate our method on the Face and Ocular Challenge Series (FOCS) Video Challenge, which consists of unconstrained video sequences. We show that our method is efficient and performs significantly better than many competitive video-based face recognition algorithms.
UR - http://www.scopus.com/inward/record.url?scp=84867849353&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867849353&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-33783-3_55
DO - 10.1007/978-3-642-33783-3_55
M3 - Conference contribution
AN - SCOPUS:84867849353
SN - 9783642337826
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 766
EP - 779
BT - Computer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings
T2 - 12th European Conference on Computer Vision, ECCV 2012
Y2 - 7 October 2012 through 13 October 2012
ER -