Improved Mean Shift real-time multiple faces tracking algorithm
一种改进的Mean Shift实时多人脸跟踪算法

A real-time multiple faces tracking algorithm based on Mean Shift algorithm was presented in this paper. An adaptive kernel window was adopted for each object, and a ranked sequential tacking strategy was proposed to solve the occlusion problem. Multi-accessory information was introduced to match the tracked objects and target windows. Furthermore, in order to improve the tracking speed and robustness, Kalman filter was introduced to predict the position of the object window. The experimental results show that the proposed multiple faces tracking algorithm can track multiple faces robustly and in real-time.