A Robust Vehicle Tracking Approach Using Mean Shift Procedure
Huan Shen, Shun Ming Li, Jian Guo Mao, Fang-chao Bo, Fang Pei Li, Hua Zhou · 2009
Object tracking using vision technology is one of the key but complex functions in navigation system of Intelligent Vehicles; it became more difficult in case of there are partial occlusions and significant clutter. A mean shift embedded approach is presents for vehicle tracking under real road scenes. The HSI model and orientation histogram are used to represent the object feature; the mean shift is employed to fast searching the mode of the potential object in a neighborhood of current frame. Experimental results demonstrate that the proposed approach is robust and validate in complicated real scenes.