A fast eye localization method for face recognition

We introduce a fast, robust, accurate eye localization algorithm. Detecting and normalizing human faces from live video streams is the first crucial step in a face verification/recognition system. The accuracy and robustness affect the performance of the following face registration and classification. To localize face regions properly, we detect eye corners by using a corner detector and Gabor wavelets. First, by applying a corner detector in skin color regions, we dramatically reduce the candidate regions for eye corners. Extracted features are represented in a semilocal manner to increase discrimination. Then, in the set of the reduced candidates, a robust feature decision algorithm based on Gabor response analysis gives accurate eye corner locations. Experimental results on real images are presented.