Object Tracking Using an Improved Kernel Method

摘要：

An improved object tracking scheme is presented based on the Kalman filter and mean-shifi approach.And this scheme is robust to disturbance and occlusion of both the object and the scene. The object is selected by using FG/BG detection and represented by its center point and probability distribution. The meanshift approach estimates the object position based on the result of the Kalman filter. A threshold of the Bhattacharyya coefficient is set to judge occlusion and when object being occluded the Kalman filter estimates the object position. Since the proposed scheme combines the space information with probability distribution,it is robust to disturbance and occlusion.

关键词： object tracking Kalman filter mean shift Bhattacharyya coefficient

作者: Yuan Chen Shengsheng Yu Weiping Sun Xiaoping Chen

作者单位: College of Computer Science & Technology Huazhong University of Science & Technology WuHan,HuBei,China,430074

会议类型: 国际会议

会议名称: The 2008 International Conference on Embedded Software and Systems Symposia(ICESS 2008)(2008国际嵌入式系统及嵌入式软件会议)

会议地点: 成都

会议语种:英文

页码: 511-515

在线出版日期: 2008-01-01（万方平台首次上网日期，不代表论文的发表时间）