Application Research Of Mean Shift Algorithm For Object Tracking

The efficient tracking of moving objects in video sequence is a typical issue in computer vision fields and is widely applied to visual surveillance, intelligent traffic,human-computer ineraction,and national defence.etc. Among many object tracking methods, Mean Shift is an efficient pattern matching algorithm,which move kernel density estimation of feature to local maximum. Because of simple Computation, very good real-time, robust for object distortion and partial occlusion, Mean Shift had become a hot topic of object tracking field. The main research tasks in this paper are described as follows.①This paper does systematical analysis and summary on Target Tracking Techniques and the status quo of Mean Shift. According on different treatment consideration of Target tracking , existing Target tracking methods are divided into two kinds:methods based on Data-driven and methods based on Model-driven. Meanwhle, the advantage and disadvantage of each method are analyzed which provide some theory support for future study.②The author has deeply researched the Mean Shift object tracking algorithm and its application in Target tracking. And, the performance of Mean Shift is analyzed and verigy. In the tracking process,the tartet area are usually determined in the first frame by user. Then object model and candidate model are established in RGB color space, and Bhattacharyya coefficient is used to measure similar. In the subsequent frames,the true place are searched iteratively by mean shft algorithm based on maximum similarity function. In the end, the author selected severral video frequency to carry on the simulation experiment. Based on the experimental results, the author has carried on the deeply analysis on condition on the computational complexity and advantages and disadvantages of algorithm. What's more important is the future research direction are also summarized and discussed.③Band strategies of Mean Shift tracking algorithm are made a deep research. In Mean Shift tracking algorithm, band Value is directly related to the quantity of object Pixels which participation calculation and mixed level of backgrouns noise. But, there are few people Investigate this problem and most researchers usually select traditional band strategy according to the customs directly. To solve this problem, this paper give a analysis of the influence of different band strategies though experimental. By comparing these strategies on track accuracy and time cost, the traditional band strategy based on half diagonal has a better effect in practical application.④A new double band strategy based on similar ellipse is put forward,and this band strategy is integrated into mean shift tracking algorithm.Through structuring an ellipse being similar with target window's inscribes ellipse, it use major axis and minor axis to identify band. This way improve Proportion of object pixel in the window,and decrease the influence of background noise effectively. Experimental Results show that this strategy has a good effect on tracking target and reducing the time cost.