Research of Face Detection Based on AdaBoost and ASM

Face Detection is an essential first step of the face recognition process, and has significant effects on face feature extraction and the effects of face recognition. Face detection has extensive research value and significance. This paper deeply researches and analysis the principle, merits and demerits of the classic AdaBoost face detection algorithm and ASM algorithm based on point distribution model, using ASM to solve the problems of face detection based on AdaBoost. Firstly, the method uses the AdaBoost algorithm to detect original face from images or video stream. Secondly it uses ASM algorithm converges, which fit face region detected by Adaboost to detect faces more accurately. Finally, it cuts out the specified size of the facial region on the basis of the positioning coordinates of eyes. The experiment results indicate that this method can detect face rapidly and precisely, with a strong robustness.