Research of real-time target tracking base on particle filter framework

被引：0

作者：

机构：

[1] College of Information Science and Engineering, Yanshan University

[2] Department of Computer Science, Shijiazhuang University

[3] State Grid Hebei Electric Power Research Institute

来源：

Liu, J. (Daishan74@126.com) | 1600年 / Binary Information Press卷 / 10期

关键词：

Camshift; EKF; Intelligent transportation; Particle filter; Target tracking;

D O I：

10.12733/jcis9640

中图分类号：

学科分类号：

摘要：

The main disadvantage of traditional particle filter algorithm is huge work quantity of computation, which is lead to poor real-time capability. We propose a real time target-tracking algorithm based on particle filter framework combined with EKF and Camshift algorithm. By choose optimized importance density function from EKF algorithm, the new algorithm can make the distribution of particles more suitable to the actual posterior distribution. Then use the Camshift algorithm to rearrange the particles, let them further cluster to the maximal posterior probability density area of the target state. Copyright © 2014 Binary Information Press.

引用

页码：2323 / 2329

页数：6

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