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Human face detection and recognition are challenged questions in pattern recognition field. After the facial features such as eyes, nose and mouth are detected in an image which contains a face, the rectangle area surrounding facial features is obtained. The pixels number of the rectangle area is large and the intensity values of these pixels are often treated as a feature vector. It is very important to drop the dimension of the vector for an effective recognition. Three means for dimensional reduction in the feature extraction field are often used, including average values of weighted intensity, wavelet transform and principle component analysis. The compact face feature vector is the eigenvector to be recognized. A face recognition method using ART2 is proposed in the paper. Experiment results show that it is preferable in recognition as well as it could increase or decrease samples rapidly.
Machine Learning and Cybernetics, 2003 International Conference on (Volume:5 )
Date of Conference: 2-5 Nov. 2003