The current project presents the development and implementation of a Facial Expression Recognition (FER) system for detecting expressions such as happiness, anger, sadness, fear, disgust, and surprise from a grayscale image. The system is implemented in MATLAB using the Gabor filter for feature extraction and the Linear Discriminant Analysis method for classification. The system has been extensively tested and evaluated using images from the Japanese Female Facial Expression (JAFFE) database and from the Cohn-Kanade (CK) database. Testing results show that depending on the expression to be detected, the success rate of the system can be as high as 95% for images coming from the JAFFE database, or as high as 80% for images coming from the CK database.
|Commitee:||Tran, Boi, Yeh, Hen-Geul|
|School:||California State University, Long Beach|
|School Location:||United States -- California|
|Source:||MAI 56/02M(E), Masters Abstracts International|
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