Manifold Analysis for Subject Independent Dynamic Emotion Recognition in Video Sequences

This paper proposes subject independent manifold features for dynamic emotion recognition. Facial action features, based on FACs, are firstly embedded into a low-dimensional manifold space using the ISOMAP algorithm, then the manifold features from different subjects are aligned into a global coordi...

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Bibliographic Details
Published in2009 Fifth International Conference on Image and Graphics pp. 896 - 901
Main Authors Fan Ping, Jiang Dongmei, Wang Fengna, Ilse, R., Hichem, S.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2009
Subjects
dynamic emotion recognition
Emotion recognition
Eyes
Facial features
Feature extraction
Graphics
Humans
Linear discriminant analysis
manifold
Mouth
Principal component analysis
Video sequences
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Summary:This paper proposes subject independent manifold features for dynamic emotion recognition. Facial action features, based on FACs, are firstly embedded into a low-dimensional manifold space using the ISOMAP algorithm, then the manifold features from different subjects are aligned into a global coordinate space by the supervised ISOMAP algorithm for recognition. To validate and evaluate the proposed manifold representation for emotion recognition, experiments with GMMs are presented. Given a new expression sequence, and tracked facial features, we are able to pin-point the actual occurrence of specific expressions, while characterizing its intensity by considering different expression temporal transition characteristics. Finally, experimental results show that our approach is able to separate different expressions successfully.
ISBN:1424452376
9781424452378
DOI:10.1109/ICIG.2009.76