Online facial expression recognition based on personalized galleries

An online facial expression recognition system based on personalized galleries is presented. This system is built on the framework of the PersonSpotter system, which is able to track and detect the face of a person in a live video sequence. By utilizing the recognition method of Elastic Graph Matching, the most similar person whose images are stored in the gallery can be found, then the personalized gallery of this person is used to recognize the expression on the probe face. A personalized gallery consists of images of the same person showing different facial expressions. Node weighting and weighted voting in addition to Elastic Graph Matching are applied to identify the expression. The performance achieved by this system shows its great potential.

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

[2]  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.

[3]  Joachim M. Buhmann,et al.  Distortion Invariant Object Recognition in the Dynamic Link Architecture , 1993, IEEE Trans. Computers.

[4]  Larry S. Davis,et al.  Computing spatio-temporal representations of human faces , 1994, 1994 Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[5]  Alex Pentland,et al.  Facial expression recognition using a dynamic model and motion energy , 1995, Proceedings of IEEE International Conference on Computer Vision.

[6]  Norbert Krüger,et al.  Face Recognition and Gender determination , 1995 .

[7]  Laurenz Wiskott,et al.  Labeled graphs and dynamic link matching for face recognition and scene analysis , 1995 .

[8]  M. Yachida,et al.  Facial expression recognition and its degree estimation , 1997, Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[9]  Hartmut Neven,et al.  PersonSpotter-fast and robust system for human detection, tracking and recognition , 1998, Proceedings Third IEEE International Conference on Automatic Face and Gesture Recognition.