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     One of the common ways of human showing emotion is through the change in facial expression. In this paper, we propose a new method for emotion detection by analyzing facial expression images. Facial expression information is analyzed by using a new feature construction method called Evolution-COnstructed(ECO) Features. The proposed algorithm is able to automatically recognize seven basic emotions that include Anger, Contempt, Disgust, Fear, Happiness, Sadness and Surprise. The test results on the Cohn-Kanade dataset show the proposed algorithm has very high classification accuracy.

Collaborators: Drs. Kirt Lillywhite and Beau Tippetts, Smart Vision Works International, LLC

Graduate Students:

Meng Zhang and Alok Desai

Publications:
  1. M. Zhang, D.J. Lee, A. Desai, K.D. Lillywhite, and B.J. Tippetts, “Automatic Facial Expression Recognition Using Evolution Constructed Features,” Lecture Notes in Computer Science, International Symposium on Visual Computing, p. 282-291, Las Vegas, NV, USA, December 8-10 2014.
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