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| Automatic Object Tracking Method Based on SAD and UKF-Mean Shift |
| LIU Xian-Ru,CAI Zi-Xing,TANG Jin |
| School of Information Science and Engineering,Central South University,Changsha 410083 |
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Abstract Aiming at the problems in accurate motion detection and tracking location under complex scene, an automatic object tracking method combined sum of absolute difference (SAD) and Mean shift with unscented Kalman filter (UKF) is proposed. Firstly block matching method based on SAD is used to estimate the displacement between current frame and successive frame. Then the disparity cues are utilized to detect the moving object automatically and build the object model and state-space model for following tracking task. Finally Mean shift with UKF is employed to filter and estimate the state of the object and locate the object in subsequence image frame. The experimental results show that the proposed moving object detection method effectively detects moving objects in scene and acquires the motion information of objects. Compared with the related methods, the proposed tracking strategy based on UKF-Mean shift has better tracking results and time property.
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Received: 20 July 2009
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2010, Vol. 23 
