Player Detection Algorithm Based on Color Segmentation and Improved CamShift Algorithm

Abstract

Aimed at the most proposed methods that detecting and tracking moving object cannot receive a good segmentation of the player in dynamic scenes, the chapter put forward an algorithm, based on color segmentation and the CamShift algorithm, to detect the tennis player. Firstly, apply a supervised clustering binary tree to automatically detect the target’s area. Secondly, take the detected area as the initial tracking window, track the target by using the improved CamShift algorithm. On the basis of accurate tracking, the chapter raises a new extraction method of the player, taking use of the characteristic that mostly the court’s color is simple. The method raises the thought that extract the player by the color feature, and it combines the CamShift algorithm with the difference in frame to overcome the tracking-loss problem. Experimental results show that our algorithm is effective in detecting the player in dynamic scenes.