Real time face recognition system using autoassociative neural network models

This paper proposes a novel method for video-based real time face recognition. The proposed method uses motion information to detect the face region, and the region is processed in YCrCb color space to determine the location of the eyes. The system extracts only the gray level features relative to the location of the eyes. Autoassociative Neural Network (AANN) model is used to capture the distribution of the extracted gray level features. Experimental results show that the proposed system gives an average recognition rate of 99% in real time for 25 subjects. The performance of the proposed method is invariant to size, tilt of the face and is also not sensitive to natural lighting conditions.