新的基于Kalman滤波的跟踪方法

模板更新策略是匹配跟踪算法成败的关键，为了提高基于模板匹配跟踪算法的性能，在分析多种模板更新算法的基础上，给出使用Kalman滤波器更新模板的方法。该方法不再将模板图像视为一个整体，而是使用Kalman滤波器对模板图像逐像素点进行更新，以得到自适应和最佳的目标模板图像，使匹配跟踪算法的性能得到很大提高，特别对于目标被遮挡、目标姿态变化以及环境照度变化有很强的适应性。对匹配算法的改进和遮挡的处理使该算法的性能得到进一步提高。实验结果表明该方法行之有效。

New tracking method based on Kalman filter

Template updating method is the key of the success of the matching and tracking algorithm. In order to improve the performance of the tracking algorithm using template matching, a new method for tracking rigid objects in image sequences is proposed after analyzing many template updating methods. A Kalman filter is used to update the template dot by dot instead of renewing it as a whole, and make it adapt to changes in object orientation, illumination and occlusion. The new method improves the performance of the image matching and tracking. The experiments testify the algorithm′s efficiency.