Object Tracking Using Improved CAMShift Algorithm Combined with Motion Segmentation

Continuously adaptive mean-shift(CAMShift) is an efficient and light-weight tracking algorithm developed based on mean-shift. While color based CAMShift is suitable for tracking targets in simple cases, it fails to track objects in more complex situations. In this paper we review our low cost extension to improve the traditional CAMShift algorithm. Combining the original algorithm with a motion segmentation phase, we proposed an improved CAMShift algorithm to cope with CAMShift's tracking problems. We evaluated the efficiency of our approach by comparing our tracking results with the traditional algorithm's results in several cases.