Abstract
Recognizing human facial expression and emotion by computer is an interesting and challenging problem. In this paper we propose a method for recognizing emotions through facial expressions displayed in video sequences. We introduce the Cauchy Naive Bayes classifier which uses the Cauchy distribution as the model distribution and we provide a framework for choosing the best model distribution assumption. Our person-dependent and person-independent experiments show that the Cauchy distribution assumption typically provides better results than the Gaussian distribution assumption.
Original language | English (US) |
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Pages (from-to) | 17-20 |
Number of pages | 4 |
Journal | Proceedings - International Conference on Pattern Recognition |
Volume | 16 |
Issue number | 1 |
State | Published - 2002 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition