Research On Technology Of Moving Target Detection And Tracking On Video Image

Motion target detection and tracking is one of the most important subjects in computer vision, which combines advanced technologies in image processing ,pattern recognition , automatic control ,artificial intelligence, and other relative fields. It has broadly applied in many aspects .So this subject research has important theoretical significance and practical value.Form the static background , this paper made value exploration and improvement on moving target detection algorithm and tracking algorithm.In the moving target detection aspect , firstly, current theories of target diction were summarized ,and analyzed their strengths and weakness. Then, the objects detection methods based on Gaussian model are analyzed and discussed in detail , and a new algorithm is proposed. The experiments results show that the proposed method can obtain a more objects detection result.In the moving target tracking aspect, this paper concludes the relative technologies, introduces temporal difference , and analyzed the advantages and disadvantages of the every method. The important studies the tracking method based on卡尔曼motion estimation and CamShift tracking method . The tracking method based-on卡尔曼motion estimation uses the motion information for tracking; The CamShift tracking method uses the color image instead of gray image. Although the convergence of Camshift tracking method is faster , if the color of moving object is similar to background ,or objects will be a serious loss of the object block, the object size changes also may result in loss tracking . The paper presented an improved CamShift algorithm, combined the卡尔曼filtering. The experimental results show that the improved algorithm to improve the moving object tracking algorithm robustness.