Research of Correlation Tracking Algorithm Based on Correlation Coefficient
基于相关系数的相关跟踪算法研究

This paper presents a correlation tracking algorithm based on correlation coefficient, which overcomes the disadvantages of traditional correlation tracking based on point-to-point multiple with accumulation and has the advantages of good accuracy and high stability. At the same time, many measures are put forward to improve the speed of the algorithm, which resolve the requirement of real-time of object tracking. And during the object-tracking, there may be many changes in a sequence of the object images, therefore, a reasonable strategy of template updating will be the key of the object-tracking problem. On the basis of the similarity measurement and template buffers, a suitable template updating strategy is given, which effectively decreases the accumulation of the object-tracking error, and greatly improves the stability of the object-tracking. The failure judgement of object-tracking presented effectively resolves the transitory failure of tracking, caused by sudden changes, such as the changes between the dark and the bright, or the tracked object is covered temporarily. The experiments show the solution decreases the complex of correlation tracking, and has the advantages of good accuracy and high speed as well. Now this algorithm has been applied to real-time object-tracking system.