Joint and Implicit Registration for Face Recognition.
CVPR: 2009 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, VOLS 1-4.
(pp. 1510 - 1517).
Contemporary face recognition algorithms rely on precise localization of keypoints (corner of eye, nose etc.). Unfortunately finding keypoints reliably and accurately remains a hard problem. In this paper we pose two questions. First, is it possible to exploit the gallery image in order to find keypoints in the probe image? For instance, consider finding the left eye in the probe image. Rather than using a generic eye model, we use a model that is informed by the appearance of the eye in the gallery image. To this end we develop a probabilistic model which combines recognition and keypoint localization. Second, is it necessary to localize keypoints? Alternatively we can consider keypoint position as a hidden variable which we marginalize over in a Bayesian manner We demonstrate that both of these innovations improve performance relative to conventional methods in both frontal and cross-pose face recognition.
|Title:||Joint and Implicit Registration for Face Recognition|
|Event:||IEEE-Computer-Society Conference on Computer Vision and Pattern Recognition Workshops|
|Location:||Miami Beach, FL|
|Dates:||2009-06-20 - 2009-06-25|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Computer Science|
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