Scholarly Research Excellence

Clark Van Dam

Publications

1

Publications

1
1686
A Hybrid CamShift and l1-Minimization Video Tracking Algorithm
Abstract:
The Continuously Adaptive Mean-Shift (CamShift) algorithm, incorporating scene depth information is combined with the l1-minimization sparse representation based method to form a hybrid kernel and state space-based tracking algorithm. We take advantage of the increased efficiency of the former with the robustness to occlusion property of the latter. A simple interchange scheme transfers control between algorithms based upon drift and occlusion likelihood. It is quantified by the projection of target candidates onto a depth map of the 2D scene obtained with a low cost stereo vision webcam. Results are improved tracking in terms of drift over each algorithm individually, in a challenging practical outdoor multiple occlusion test case.
Keywords:
CamShift, l1-minimization, particle filter, stereo vision, video tracking.