基于灰度投影变换的改进Mean-shift算法

Mean-shift algorithm with adjustive based on ray-scale projection transformation

针对传统的均值漂移算法中核窗宽无法实时适应运动目标大小变化的问题,提出一种改进的Mean-shift跟踪算法。该算法通过对数坐标变换后的目标图像以及候选图像进行灰度投影计算,得到两幅图像的相对位移量,从而计算出窗口缩放因子,以便对核窗宽进行调整。实验证明,该算法可以有效地提高Mean-shift算法跟踪的准确性。

For the problem that bandwidth of the traditional target tracking algorithm based on Mean shift is unable to adapt to the size changes of moving targets in real time,an improved Mean shift tracking algorithm is proposed. This algorithm by calculating the gray-scale projection of the target image and the candidate image after their log-polar coordinate transformation obtains the relative displacement of the two images,and calculates the scale factor to adjust the bandwidth. The experimental results show that the proposed algorithm can improve the accuracy of Mean-shift tracking algorithm.