Research On The Key Technologies Of Moving Object Detection And Tracking In Video Surveillance

Motion object detection and tracking in serial images is the main research field in Video Surveillance, which has been widely applied in military, medicine and scientific research etc. The accuracy and stability of tracking effect depend on the design of algorithms to a great extent. The key technologies is studied in this paper about how to detect and track moving object in Video Surveillance.On the research of the motion detection, firstly three main algorithms of motion detection and its analyzed advantages and drawbacks are researched. Secondly, background estimation based on block is proposed to solve the problem of Obtaining and estimating and updating background model which can enhance the robust of moving object detection. A background modeling and subtraction method by codebook construction is proposed. The CB algorithm adopts a quantization and clustering technique to construct a background model and subtract the current image from the background model to detect moving objects by color distortion and bright distortion. Evaluation shows that this algorithm is effective.On the research of object tracking, firstly some common used algorithms of are researched. Then a new method of moving object tracking based on the result of image subtraction and object features matching is presented. The obtained object is framed and its center of gravity is calculated. In this together with its shape feather, its moving path can be obtained. Evaluation shows that this algorithm has better adoption in case of a little shape change and is effective in simple cases. At last the Mean Shift Algorithm is analyzed from the aspects of realization principle and match criterion and search algorithm.