A Robust Object Tracking Approach based on Mean Shift Algorithm

摘要

Object tracking has always been a hotspot in the field of computer vision, which has a range of applications in real word. The object tracking is a critical task in many vision applications. The main steps in video analysis are two: detection of interesting moving objects and tracking of such objects from frame to frame. Most of tracking algorithms use pre-defined methods to process. In this study, we introduce the Mean shift tracking algorithm, which is a kind of important no parameters estimation method, then we evaluate the tracking performance of Mean shift algorithm on different video sequences. Experimental results show that the Mean shift tracker is effective and robust tracking method.