Emotion Recognition Using a Cauchy Naive Bayes Classifier

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.

• Type: Conference
• Year: 2002
• Where: ICPR
• Authors: Nicu Sebe, Michael S. Lew, Ira Cohen, Ashutosh Garg, Thomas S. Huang
• Keywords: Cauchy Distribution Assumption, Computer Vision, Gaussian Distribution Assumption, ICPR 2002, Model Distribution Assumption