Recognizing human facial expression and emotion by computer is an interesting and challenging problem. We propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce a tree-augmented naive-Bayes (TAN) classifier that learns the dependencies between facial features; we also provide an algorithm for finding the best TAN structure. Our person-dependent and person-independent experiments show that using this TAN structure provides significantly better results than using simpler NB-classifiers.

Facial Expression Recognition from Video Sequences

Sebe, Niculae;
2002-01-01

Abstract

Recognizing human facial expression and emotion by computer is an interesting and challenging problem. We propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce a tree-augmented naive-Bayes (TAN) classifier that learns the dependencies between facial features; we also provide an algorithm for finding the best TAN structure. Our person-dependent and person-independent experiments show that using this TAN structure provides significantly better results than using simpler NB-classifiers.
2002
Proceedings of the IEEE International Conference on Multimedia and Expo
345 E 47TH ST, NEW YORK, NY 10017 USA
Institute of Electrical and Electronics Engineers Inc.
0780373049
I., Cohen; Sebe, Niculae; A., Garg; M. S., Lew; T. S., Huang
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11572/94014
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