Computing spatio-temporal representations of human faces

An approach for analysis and representation of facial dynamics for recognition of facial expressions from image sequences is proposed. The algorithms we develop utilize optical flow computation to identify the direction of rigid and non-rigid motions that are caused by human, facial expressions. A mid-level symbolic representation that is motivated by linguistic and psychological considerations is developed. Recognition of six facial expressions, as well as eye blinking, on a large set of image sequences is reported.<<ETX>>

[1]  P. Ekman.  Unmasking The Face , 1975 .

[2]  H. Ellis.  Recognizing faces. , 1975, British journal of psychology.

[3]  J. N. Bassili.  Emotion recognition: the role of facial movement and the relative importance of upper and lower areas of the face. , 1979, Journal of personality and social psychology.

[4]  P. Ekman,et al.  Approaches To Emotion , 1985 .

[5]  A. Young,et al.  Handbook of Research on Face Processing , 1989 .

[6]  Alan L. Yuille,et al.  Feature extraction from faces using deformable templates , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[7]  Kenji Mase,et al.  Recognition of Facial Expression from Optical Flow , 1991 .

[8]  Larry S. Davis,et al.  Labeling of human face components from range data , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[9]  Pertti Roivainen,et al.  3-D Motion Estimation in Model-Based Facial Image Coding , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Xiaobo Li,et al.  Towards a system for automatic facial feature detection , 1993, Pattern Recognit..

[11]  Azriel Rosenfeld,et al.  Binocular motion stereo using MAP estimation , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[12]  Demetri Terzopoulos,et al.  Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models , 1993, IEEE Trans. Pattern Anal. Mach. Intell..