Facial Feature Detection And Tracking Algorithm

The problem of facial feature detection and tracking, a key technology in face information processing, has recently emerged into an important subject in the fields of pattern recognition and computer vision.Based on a general review of existing schemes on this particular topic, we discuss two facial feature detection algorithms and two tracking algorithms. The first detection method is based on facial knowledge and edge extracting, which localizes eyes and mouse roughly using morphologic processing and area filter, and then extracts canthi and corners of the mouth accurately using Canny edge extracting method. The other detection algorithm is based on an eye model, which first uses a statistical skin-color model to segment face-candidate regions in the image, and the presence or absence of a face in each region is verified by means of an eye detector, based on an efficient template matching scheme. For the two facial feature tracking algorithms, the former approach uses simple template matching to search eyes and mouse in the current frame. The second tracking method synthesizes deformable template and snake, which localizes feature contours using deformable template, then convergences to the accurate feature contours using snake. Later, we discuss mouse tracking based on double snakes.Finally, several further research aspects are pointed out based on the analysis of the cons and pros of the above four algorithms...