An object tracking algorithm combining spatial structure and motion continuity

Abstract

To deal with the tracking drift problems caused by drastic object appearance change in complex scene, the paper proposes a robust tracking algorithm based on the sparse representation. It designs an optimized objective function with the spatial structure constraint. And then, with the Lagrange multiplier theory and accelerate proximal gradient approach, the coefficient of object template and candidate with the spatial information is obtained. In addition, the histogram intersection theory is exploited to computer the similarity between candidate and template. Finally, the template update scheme about when to manage updating and how to realize the strategy is presented, which combines the spatial structure information together with motion continuity and enables to tackle appearance change effectively. Experimental results on challenging benchmark datasets demonstrate that the novel algorithm performs favorable against several state-of-the-art methods.