Abstract: A new method for face detection and tracking in sequential moving state was proposed. The FloatBoost algorithm was used for face detecting to enhance its speed and accuracy. Then, based on the theory of kinematics and motion estimation, the motion averaging method and exponential smoothing method in time-series analysis were used to predict the moving location area of tracking object in next frame image so as to reduce the searching region and decrease the consumption of processing resource, thus implementing the real-time tracking effect. In the face detecting/tracking simulation by MATLAB the algorithm proposed was compared with the FSA and CPME algorithms in respect to the time required for tracking an object, and the results showed that the former is superior to the latter two in real-time response and accuracy.