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16th International Conference on Pattern Recognition (ICPR'02) - Volume 1
Emotion Recognition Using a Cauchy Naive Bayes Classifier
Quebec City, QC, Canada
August 11-August 15
ISBN: 0-7695-1695-X
Nicu Sebe, Leiden Institute of Advanced Computer Science
Michael S. Lew, Leiden Institute of Advanced Computer Science
Ira Cohen, University of Illinois at Urbana Champaign
Ashutosh Garg, University of Illinois at Urbana Champaign
Thomas S. Huang, University of Illinois at Urbana Champaign
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.
Citation:
Nicu Sebe, Michael S. Lew, Ira Cohen, Ashutosh Garg, Thomas S. Huang, "Emotion Recognition Using a Cauchy Naive Bayes Classifier," icpr, vol. 1, pp.10017, 16th International Conference on Pattern Recognition (ICPR'02) - Volume 1, 2002
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