To deal with the problem of tracking person with a mobile robot in dynamic scene with occlusion, a tracking system is presented in this paper. We focus on the individual person tracking system, which is applied on our two-wheel mobile robot with a single PTZ (pan-tilt-zoom) camera. The tracking system works reliably in the dynamic environment with partial/complete occlusion. For the sake of complete occlusion, we use several filters and spatial relation restriction to represent the target model. These filters are all based on the appearance of the target, and each filter models a part of human body which is more rigid than the entire body. To construct a tracking system, the situation-based strategy and a simple frame-to-frame tracker are involved in the system, and an improved mean-shift tracking algorithm is applied as the tracker in this paper. Finally, experimental results on tracking individual person with complete occlusion in different environments are shown, which demonstrate the robustness and effectiveness of the algorithm

Gilbert algorithm is a very popular algorithm in collision detection in robotics and also in classification in pattern recognition. However, the major drawback of Gilbert algorithm is that in many cases it becomes very slow as it approaches the final solution and the vertices selection vibrates in these cases. In this paper: a) It is proven theoretically that when the selection of vertices vibrates among several points, the algorithm will converge to the hyperplane determined by these points. b) Based on the above results, an improved Gilbert algorithm for computing the distance between two convex polytopes is presented. The algorithm can avoid the slow convergence of the original one. Numerical simulation results demonstrate the effectiveness and advantage of the improved algorithm