Abstract:

In order to balance the detection quality and the computing speed of the existing human face-detecting methods, an algorithm for face detection and feature location of moving men in a video is proposed. In this algo- rithm, first, the approximate face region is detected using the Adaboost method. ＇Next, the specific face region is determined using the skin color model, and the face part is picked up from the frame. Then, the video frame with a high face-region definition and a region as large as possible is selected by judging the image definition from the Peak Signal-to-Noise Ratio （PSNR） based on the difference between two neighbor frames in face region. Finally, the face detection and feature location of the video frame are performed. Experimental results indicate that, as com- pared with the existing face-detecting methods, the proposed method helps to perform more accurate feature location for corners of eye and mouth with higher calculating speed, the face-detecting rate being about 94.8%.

Key words: video processing, face detection, feature location, image definition, Peak Signal-to-Noise Ratio, skin color model