Target Tracking Algorithm Based on Meanshift and Kalman Filter

被引：0
作者：
Li H. [1 ]
Zhu J. [1 ]
机构：
[1] College of Information and Computer, Taiyuan University of Technology, Jinzhong, 030600, Shanxi
来源：
Journal of Beijing Institute of Technology (English Edition) | 2019年 / 28卷 / 02期
关键词：
Kalman algorithm; Meanshift algorithm; Target tracking;
D O I：
10.15918/j.jbit1004-0579.17180
中图分类号：
学科分类号：
摘要：
Directed at the problem of occlusion in target tracking, a new improved algorithm based on the Meanshift algorithm and Kalman filter is proposed. The algorithm effectively combines the Meanshift algorithm with the Kalman filtering algorithm to determine the position of the target centroid and subsequently adjust the current search window adaptively according to the target centroid position and the previous frame search window boundary. The derived search window is more closely matched to the location of the target, which improves the accuracy and reliability of tracking. The environmental influence and other influencing factors on the algorithm are also reduced. Through comparison and analysis of the experiments, the modified algorithm demonstrates good stability and adaptability, and can effectively solve the problem of large area occlusion and similar interference. © 2019 Editorial Department of Journal of Beijing Institute of Technology .
引用
收藏
页码：365 / 370
页数：5
相关论文
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