Non-rigid Object Tracking as Salient Region Segmentation and Association

Abstract

Tracking a non-rigid object in a video in the presence of background clutter and partial occlusion is challenging. We propose a non-rigid object-tracking paradigm by repeatedly detecting and associating saliency regions. Saliency region segmentation is operated in each frame. The segmentation results provide rich spatial support for tracking and make the reliable tracking of non-rigid object without drifting possible. The precise object region is obtained simultaneously by associating the saliency region using two independent observers. Our formulation is quite general and other salient-region segmentation algorithms also can be used. Experimental results have shown that such a paradigm can effectively handle tracking problems of objects with rapid movement, rotation and partial occlusion.