A 3D Facial Expression Database For Facial Behavior Research
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Expression-Invariant Face Recognition with Expression Classification
CRV '06 Proceedings of the The 3rd Canadian Conference on Computer and Robot Vision
Accurate optical flow computation under non-uniform brightness variations
Computer Vision and Image Understanding
Expression-invariant face recognition with accurate optical flow
PCM'07 Proceedings of the multimedia 8th Pacific Rim conference on Advances in multimedia information processing
Recognizing expression variant faces from a single sample image per class
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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Face recognition is one of the most intensively studied topics in computer vision and pattern recognition. A constrained optical flow algorithm, which combines the advantages of the unambiguous correspondence of feature point labeling and the flexible representation of optical flow computation, has been proposed in our pervious work for face recognition from expressional face images. In this paper, we propose an integrated face recognition system that is robust against facial expressions by combining information from the computed intra-person optical flow and the synthesized face image in a probabilistic framework. Our experimental results show that the proposed system improves the accuracy of face recognition from expressional face images.