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. © 2002 IEEE.
Emotion Recognition Using a Cauchy Naïve Bayes Classifier
Sebe, Niculae;
2002-01-01
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. © 2002 IEEE.File in questo prodotto:
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