Visual Target Tracking Based on Particle Filter and Local Search

ZHANG Nan; LIU Cheng-zhi; FAN Cun-bo; HAH Xing-wei; LI Zhen-wei; SUN Ming-guo

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Visual Target Tracking Based on Particle Filter and Local Search

更新时间：2026-09-04

- Visual Target Tracking Based on Particle Filter and Local Search
- Vol. 30, Issue 9, Pages: 1-4(2013)
- 作者机构：
  
  中国科学院机构国家天文台长春人造卫星观测站,吉林,长春,130117
- 作者简介：
- 基金信息：
- DOI：
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- Published：2013
- 稿件说明：
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张楠, 刘承志, 范存波, 韩兴伟, 李振伟, 孙明国. 基于粒子滤波与局部搜索的视频目标跟踪[J]. 微电子学与计算机, 2013, 30(9): 1-4.

ZHANG Nan, LIU Cheng-zhi, FAN Cun-bo, et al. Visual Target Tracking Based on Particle Filter and Local Search[J]. 2013, 30(9): 1-4.
张楠, 刘承志, 范存波, 韩兴伟, 李振伟, 孙明国. 基于粒子滤波与局部搜索的视频目标跟踪[J]. 微电子学与计算机, 2013, 30(9): 1-4. DOI：

ZHANG Nan, LIU Cheng-zhi, FAN Cun-bo, et al. Visual Target Tracking Based on Particle Filter and Local Search[J]. 2013, 30(9): 1-4. DOI：

摘要

为了提高视频目标跟踪的鲁棒性和准确性，本文提出了基于局部搜索(Local Search)和粒子滤波(Particle Filter)相结合的视频目标跟踪方法——LSPF (Local Search Particle Filter)算法.利用粒子滤波得到样本的权值后，将局部搜索用于每一个粒子，使权值小的粒子收敛于邻近的权值较大的粒子处，有效克服了传统PF算法的粒子退化问题.实验结果表明，传统PF算法平均跟踪误差为10.89，而本文提出的LSPF算法平均跟踪误差仅为3.49，在跟踪性能上有了很大改善.尤其当目标受到干扰时，LSPF算法仍能实现对目标的准确跟踪，为稳定跟踪提供了有利保障.

Abstract

In order to improve the tracking accuracy and robustness

LSPF (Local Search Particle Filter) is proposed that is the visual target tracking algorithm based on the combination of particle filter (PF) and local search (LS). After weight of each sample is obtained by particle filter

local search analysis is applied to each sample to make the samples of small weight converge at that of large weight that overcomes degeneracy problem efficiently.The experimental results show that the average tracking error of standard PF algorithm is 10.89

however

the average tracking error of the new algorithm is only 3.49

and tracking performance is improved evidently.Especially

when the target is interfered

it can be accurately tracked with LSPF algorithm which ensures advantageously the stability of tracking.

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Related Institution

Department of Weapon Science and Technology, NAEI

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