Robust and efficient fragments-based tracking using mean shift
Representing a target with multiple image fragments has been used for tracking in a video sequence and proved to be able to preserve the spatial information. However, this kind of target description poses additional challenges in terms of efficiency of a video target tracking. In this paper, we present a novel algorithm that addresses this issue. We propose a fusion scheme to fuse multiple spatially distributed fragments effectively. Under the fusion scheme, we derive a mean shift type algorithm which allows efficient target tracking with very low computational overhead. In order to properly fragment the human target, we propose a GrabCut-based method to divide the target into multiple distinctive fragments. The proposed algorithm is evaluated on extensive challenging sequences. The experimental results demonstrate that it is effective and efficient.
mean shift fusion scheme fragment-based tracking grabcut-based fragmentation