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论文:2013,Vol:31,Issue(6):967-973 |
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引用本文： |
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朱良谊, 王庆. 一种基于粒子滤波的优化目标跟踪算法研究[J]. 西北工业大学 |
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Zhu Liangyi, Wang Qing. An Optimized Particle Filter Based Object Tracking Algorithm[J]. Northwestern polytechnical university |
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| 一种基于粒子滤波的优化目标跟踪算法研究 |
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| 朱良谊1,2, 王庆1 |
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1. 西北工业大学 计算机学院, 陕西 西安 710072;
2. 空军工程大学 理学院, 陕西 西安 710051 |
| 摘要: |
| 基于粒子滤波提出了一种优化的目标跟踪算法——PFTMT算法。PFTMT算法在粒子滤波算法抗遮挡性强基础上结合了模板匹配算法跟踪精度高的优点,同时克服了2种算法各自的缺点,即该算法在保留粒子滤波算法的抗遮挡性强的基础上提高了粒子滤波算法的跟踪精度。PFTMT算法首先使用粒子滤波算法对目标进行大致定位,在该定位结果的基础上小范围进行模板匹配,与目标模板相似度最大的位置就是目标的精确定位。PFTMT算法的时间复杂度虽然略高于粒子滤波算法,但是可以满足目标实时跟踪的要求。实验结果验证了PFTMT算法的有效性。 |
| 关键词:
粒子滤波
模板匹配
视觉跟踪
PFTMT算法
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| An Optimized Particle Filter Based Object Tracking Algorithm |
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| Zhu Liangyi1,2, Wang Qing1 |
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1. School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an 710072 China;
2. College of Science, Air Force Engineering University, Xi'an 710051 China |
| Abstract: |
| An optimized object tracking algorithm based on particle filter and template matching is proposed in this paper.The proposed PFTMT (Particle Filter and Template Matching based Tracking ) algorithm integrates both the merit of the anti-occlusion of the particle filter and that of the high accuracy of the template matching.Firstly, standard particle filter algorithm is used to roughly locate the object in current frame.Then, template matching is done in the local region to find the accurate object location which corresponds to the local maxima similarity value between candidate and template.The time complexity of the proposed algorithm is a little higher than standard parti-cle filter, but it can still meet the requirement of real-time tracking application.Experimental results and their anal-ysis have demonstrated preliminarily the effectiveness of our approach. |
| Key words:
algorithm
efficiency
error analysis
flowcharting
location
Markov processes
probability distributions
optimization
pixels
target tracking
template matching
particle filter
PFTMT algorithm
visual tracking
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| 收稿日期: 2013-04-02
修回日期:
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| DOI: |
| 基金项目: 航空科学基金(2011ZC53036)资助 |
| 通讯作者:
Email： |
| 作者简介: 朱良谊(1973-),西北工业大学博士研究生,主要从事计算机视觉及模式识别研究。
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| 相关功能 |
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| 作者相关文章 |
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| 朱良谊 在本刊中的所有文章 |
| 王庆 在本刊中的所有文章 |
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