Abstract: A fast moving target detection method based on Mean Shift was proposed for the problems that the Mean Shift algorithm is difficult to track fast moving objects,the number of iterations of the algorithm is too large and the process is time consuming.The method is combined with frame difference method and fuses background information for rapid detection of moving target.A new similarity measure method for preliminary testing was put forward to exclude the interference and fast select targets in accordance with the standard Mean Shift matching,finding out the best target.This method not only reduces the number of iterations of the traditional method,but also reduces the time required for the algorithm,and it achieves better tracking performance in the tracking experiment,which improves the robustness of the algorithm.

Key words: Mean Shift algorithm,Frame difference method,Target tracking,Fast tracking,Robustness