Motion Targets Tracking Algorithm Based on Video Surveillance

Motion targets tracking is an important part of video surveillance,which offers technical support for researching motion characteristic and traffic behaviors of moving objects in traffic flow.Firstly,we predict the moving target state information of the former observation time by Kalman filter,and obtain the geometric center and the compactness of the object;then calculate the velocity and the compactness variety with matching errors between predicted values of the former time and observed values of the current time.From these step,we can achieve accurate,fast motion tracking results through recursive algorithm.In order to ensure the continuity and the stabilization in the tracking process,occlusion handling method based on gray model(GM(1,1)) is proposed.At last,we validate the proposed algorithm under different traffic scenes.Results show that the algorithm is robust and adaptive in multiple targets motion tracking even in the case of occlusion in real-time.