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)|
|Number of pages||4|
|Journal||Proceedings - International Conference on Pattern Recognition|
|State||Published - 2002|
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition