An image-tracking algorithm based on object center distance-weighting and image feature recognition

A real-time image-tracking algorithm is proposed, which gives small weights to pixels farther from the object center and uses the quantized image gray scales as a template. It identifies the target’s location by the mean-shift iteration method and arrives at the target’s scale by using image feature recognition. It improves the kernel-based algorithm in tracking scale-changing targets. A decimation method is proposed to track large-sized targets and real-time experimental results verify the effectiveness of the proposed algorithm.