Local Facial Asymmetry for Expression Classification

2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04) - Volume 2 pp. 889-894
Local Facial Asymmetry for Expression Classification
Sinjini Mitra, Carnegie Mellon University
Yanxi Liu, Carnegie Mellon University

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DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CVPR.2004.151
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Abstract
We explore a novel application of facial asymmetry: expression classification. Using 2D facial expression images, we show the effectiveness of automatically selected local facial asymmetry for expression recognition. Quantitative evaluations of expression classification using local asymmetry demonstrate statistically significant improvements over expression classification results on the same data set without explicit representation of facial asymmetry. A comparison of discriminative local facial asymmetry features for expression classification versus human identification is given.
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Citation: Sinjini Mitra, Yanxi Liu, "Local Facial Asymmetry for Expression Classification," cvpr, pp. 889-894, 2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04) - Volume 2, 2004

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