利用Kalman滤波的视频运动目标跟踪(英文)  

Tracking Moving Objects in MPEG Videos via Kalman Filtering

作　　者：周道兵[1] 骆鹏[2] 肖国强[1] 张贝贝[1] 

机构地区：[1]西南大学计算机与信息科学学院,重庆400715 [2]西南大学新闻传媒学院,重庆400715

出　　处：《西南师范大学学报（自然科学版）》2009年第6期113-118,共6页Journal of Southwest China Normal University(Natural Science Edition)

基　　金：重庆市自然科学基金项目(CSTC-2008BB2252)~~

摘　　要：提出一种基于kal man滤波的视频运动目标跟踪算法,首先对视频运动目标进行分割,求出运动目标的形心,再利用视频运动目标的形心所在宏块的运动矢量信息,用kal man滤波对运动目标的形心在下一帧的位置进行预测,从而快速、有效地自动跟踪多个目标对象.实验结果表明,该算法对运动目标的出现和消失,以及非刚性物体的尺度变化和变形,具有较强的鲁棒性.In this paper, based on Kalman filtering a video object tracking algorithm is presented. While existing video object tracking is sensitive to the accuracy of object segmentation, the proposed algorithm uses an object central point to complete the object tracking which allows the inaccuracy of object segmentation. Firstly, the authors extract a central point within each segmented object. In tracking step, a motion model is constructed to set system model of Kalman filtering, while the motion vectors of the macroblocks including corresponding central points are al- so extracted and normalized. Then the position of each central point in the next frame is predicted with Kalman filtering to implement the video object tracking. Since the overall object tracking is carried out via tracking the central point of each object, the proposed algorithm is tolerant to the inaccuracy of object segmentation. Experiments carried out show that the proposed algorithm works well in tracking video objects.

关 键 词：视频跟踪 形心 KALMAN滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]