Birth intensity estimation method for multi-target video tracking

被引：0

作者：

Zhou, Xiaolong ^{[1
]}

Shen, Henghua ^{[2
]}

He, Bingwei ^{[2
]}

机构：

[1] College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou,310023, China

[2] School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou,350108, China

来源：

Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer Graphics | 2014年 / 26卷 / 12期

关键词：

Probability density function - Clutter (information theory) - Probability distributions - Entropy - Estimation - Kalman filters - Video recording - Bandpass filters;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper, an effective birth intensity estimation method that based on entropy distribution and coverage rate is proposed for multi-target video tracking. The birth intensity is first initialized according to the previously obtained target states and measurements. The currently obtained measurements are then used to update the initialized birth intensity. In the updating stage, the negative exponent entropy distribution that depends on the weight is first selected as the prior distribution of the birth intensity. By doing so, the components within the birth intensity those are irrelevant to the measurements could be regarded as noises and should be removed. The coverage rate between each birth intensity component and the corresponding measurement is then computed to further eliminate those components whose weights are smaller than the given threshold. Experiments on noisy video sequences are conducted to show that the proposed birth intensity estimation method can effectively eliminate the noises and finally improve the tracking accuracy. ©, 2014, Institute of Computing Technology. All right reserved.

引用

页码：2223 / 2231