Tracking Objects through Occlusions Using Improved Kalman Filter

摘要：

In a visual surveillance system, robust tracking of moving objects which are partially or even fully occluded is very difficult. In this paper, we present a method of tracking objects through occlusions using a combination of Kalman filter and color histogram. By changing covariance of process noise and measurement noise in Kalman filter, this method can maintain the tracking of moving objects before, during, and after occlusion. Experiments which described on several test sequences of the open PETS2000 and PETS2001 datasets have demonstrated the effectiveness and robustness of this method.

关键词： tracking occlusion Kalman filter color histogram

作者: Jin Wang Fei He Xuejie Zhang Yun Gao

作者单位: School of Information Science and Technology Yunnan University Kunming,China

会议类型: 国际会议

会议名称: The 2nd IEEE International Conference on Advanced Computer Control(第二届先进计算机控制国际会议 ICACC 2010)

会议地点: 沈阳

会议语种:英文

页码: 223-228

在线出版日期: 2010-03-27（万方平台首次上网日期，不代表论文的发表时间）