一种尺度和方向适应性的Mean Shift跟踪算法

Scale and Orientation Adaptive Mean Shift Tracking

针对原始的Mean Shift跟踪算法虽能准确地估计目标位置,但对目标尺度和方向不能实现自适应估计,结合目标模型与候选目标区域的候选模型得到了反向投影图,此反向投影图可表示图像中像素点属于目标的概率,将反向投影图的矩特征应用到原始Mean Shift跟踪算法框架,实现了目标尺度和方向适应性Mean Shift跟踪.实验结果表明:该算法能有效跟踪尺度和方向变化的目标.

Although the position of target can be well obtained by the original mean shift tracking algorithm,the target＇s scale and orientation can not be estimated adaptively. This paper proposed an improved mean shift algorithm to address the issue of how to estimate target＇s variation of scale and orientation. Firstly,by combining the target mode and the candidate model,we obtain the weight image which represents the possibility that a pixel belongs to the target. Then the moment features of the weight image are applied in the mean shift tracking framework,so that the scale and orientation changes of the target can be adaptively estimated. The experimental results demonstrate the effectiveness of the proposed algorithm when tracking the target with changes in scale and orientation.