[1]陈真,王钊.元认知粒子滤波目标跟踪算法[J].智能系统学报,2015,10(3):387-392.[doi:10.3969/j.issn.1673-4785.201405052]
CHEN Zhen,WANG Zhao.Object tracking algorithm with metacognitive model-based particle filters[J].CAAI Transactions on Intelligent Systems,2015,10(3):387-392.[doi:10.3969/j.issn.1673-4785.201405052]
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CHEN Zhen,WANG Zhao.Object tracking algorithm with metacognitive model-based particle filters[J].CAAI Transactions on Intelligent Systems,2015,10(3):387-392.[doi:10.3969/j.issn.1673-4785.201405052]
元认知粒子滤波目标跟踪算法
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
10
期数:
2015年第3期
页码:
387-392
栏目:
学术论文—机器学习
出版日期:
2015-06-25
- Title:
- Object tracking algorithm with metacognitive model-based particle filters
- Keywords:
- object tracking; particle filter; metacognition; metacognitive model; metacognitive particle filter (MCPF)
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 经典粒子滤波算法进行复杂背景下的目标跟踪时,不能及时将突变的背景信息更新到目标模板中,容易造成跟踪不稳定,尤其是当突变背景与目标模板相似时,容易造成目标丢失.为了解决此类问题,提出了具有元认知能力的粒子滤波(MCPF)目标跟踪算法.首先,MCPF对初始化目标模板进行认知,建立目标认知模板和背景认知模板作为MCPF的元认知知识成分,然后,MCPF监控多次迭代后采样粒子的观测信息,刺激产生MCPF元认知体验成分,从而有效地调节MCPF算法的决策机制.实验结果表明,该算法跟踪实时性高、稳定、可靠,当背景发生突变时,能够及时监控到突变,并快速调节决策机制,实现稳定的目标跟踪.
- Abstract:
- Traditional particle filter object tracking in complex backgrounds cannot update the sudden backgrounds information to the target template timely. Therefore, it is easy to cause tracking instability, even lose object when the sudden background is similar to the target template. An object tracking algorithm with metacognitive particle filters (MCPF) is proposed to solve this problem. Firstly, MCPF establishes metacognitive knowledge composed of object cognitive models and background cognitive model. Next, MCPF monitors the observation information of the sampling particles after multiple iterations, simulates the observation information to generate metacognitive experience and realizes object-tracking stability. Extensive experimental results showed that the proposed algorithm improves the instantaneity, stability and reliability of traditional PF object tracking algorithm. When the background suddenly changes, it can timely monitor it and quickly adjust decision-making mechanism to realize stable target tracking.
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备注/Memo
收稿日期:2014-5-23;改回日期:。
基金项目:中央高校基本科研业务费专项资金(11CX04045A).
作者简介:陈真,女,1975年生,高级工程师,主要研究方向为信号处理、模式识别、人工智能.王钊,男,1976年生,副教授,主要研究方向为非线性系统.
通讯作者:陈真. E-mail: chen_zhen_09@163.com.
更新日期/Last Update:
2015-07-15