Emotion recognition using a cauchy naive bayes classifier

Nicu Sehe, Michael S. Lew, Ira Cohen, Ashutosh Garg, Thomas S. Huang

Research output: Contribution to journalArticlepeer-review

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 languageEnglish (US)
Pages (from-to)17-20
Number of pages4
JournalProceedings - International Conference on Pattern Recognition
Volume16
Issue number1
StatePublished - Dec 1 2002

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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