The study and implementation of real-time face recognition and tracking system

During the past several years, face recognition in video has received significant attention. For the video monitoring and artificial vision, real time face recognition has very important meaning. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use AdaBoost Cascade for face detection and then in order to recognize the candidate faces, they will be analyzed by the hybrid Wavelet and LDA method. After that, Mean shift will be invoked to track the face. The implementation shows that the algorithm has quite good performance in terms of real-time and the tracking procedure is triggered accurately.