Real-time Follow-up Tracking Fast Moving Object with an Active Camera

被引:0
|
作者
Xiang, Guishan [1 ]
机构
[1] Zhejiang Univ Sci & Technol, Sch Informat & Elect Engn, Hangzhou, Zhejiang, Peoples R China
来源
PROCEEDINGS OF THE 2009 2ND INTERNATIONAL CONGRESS ON IMAGE AND SIGNAL PROCESSING, VOLS 1-9 | 2009年
关键词
Mean Shift; Kalman filter; region of interest; follow-up tracking;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A method for real-time follow-up tracking fast moving object with an active camera is proposed. The Mean Shift algorithm shows an excellent performance on robust and fast object tracking; however, it is prone to fail when tracking a very fast moving object. This paper addresses to solve the problem. At first Mean Shift based on the color feature of the object is introduced. The object maybe can't be tracked when the motion of the object or the motion of the active camera is very fast. In order to overcome this difficulty, Kalman filter is introduced to predict the location of the initial search window of Mean Shift. In order to reduce the disturbance from the background and to reduce the computational consumption, a region of interest (ROI) is introduced. To follow-up track the moving object smoothly, a closed loop control model based on speed regulation is applied to drive a PTZ camera to center the target. The results of our experiments show that the active camera can follow-up track a fast moving object smoothly. The system is computationally efficient and can run in real-time speed.
引用
收藏
页码:2076 / 2079
页数:4
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