Swarm intelligence based object tracking

Though object tracking is a very old problem still there are several challenges to be solved; for instance, variation of illumination of light, noise, occlusion, sudden start and stop of moving object, shading etc. In this paper we propose a dual approach for object tracking based on optical flow and swarm Intelligence. The optical flow based KLT tracker, tracks the dominant points of the target object from first frame to last frame of a video sequence; whereas swarm Intelligence based PSO tracker simultaneously tracks the boundary information of the target object from second frame to last frame of the same video sequence. The boundary information of the target object is captured by the polygonal approximation of the same. The dual approach to object tracking is inherently robust with respect to the above stated problems. We compare the performance of the proposed dual tracking algorithm with several benchmark datasets and in most of the cases we obtain superior results.