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一种基于卡尔曼滤波及粒子滤波的目标跟踪算法
引用本文:杜超,刘伟宁,刘恋. 一种基于卡尔曼滤波及粒子滤波的目标跟踪算法[J]. 液晶与显示, 2011, 26(3): 384-389. DOI: 10.3788/YJYXS20112603.0384
作者姓名:杜超  刘伟宁  刘恋
作者单位:1. 中国科学院长春光学精密机械与物理研究所,吉林长春130033;中国科学院研究生院,北京100039
2. 中国科学院长春光学精密机械与物理研究所,吉林长春,130033
摘    要:针对卡尔曼跟踪算法在非线性非高斯情况下跟踪结果不再准确,以及粒子滤波跟踪算法计算量大难以满足实时性的缺陷,提出了卡尔曼滤波及粒子滤波相结合的算法。利用卡尔曼滤波进行跟踪得到候选目标并计算目标模型与候选模型的匹配程度,若与目标模型匹配度小于一定阈值,则转换跟踪方式利用粒子滤波进行跟踪来修正卡尔曼滤波结果;同时,采用"模板缓冲区法"对目标模型进行更新以保证跟踪的连续性、稳定性及准确性。实验结果表明,这种跟踪算法既发挥了卡尔曼滤波的实时性又保持了粒子滤波的准确性,有较好的跟踪性能。

关 键 词:目标跟踪  卡尔曼滤波  粒子滤波  模板更新

Target Tracking Algorithm Based on Kalman Filter and Particle Filter
DU Chao,LIU Wei-ning,LIU Lian. Target Tracking Algorithm Based on Kalman Filter and Particle Filter[J]. Chinese Journal of Liquid Crystals and Displays, 2011, 26(3): 384-389. DOI: 10.3788/YJYXS20112603.0384
Authors:DU Chao  LIU Wei-ning  LIU Lian
Affiliation:DU Chao1,2,LIU Wei-ning1,LIU Lian1,2*(1.Changchun Institute of Optics,Fine Mechanics and Physics,Chinese Academy of Sciences,Changchun 130031,China,2.Graduate University of Chinese Academy of Sciences,Beijing 100039,China)
Abstract:Aiming at the problem that Kalman filter tracking algorithm is no longer accurate in non-Gauss and non-linear case and the Particle filter tracking algorithm costs huge computation,a improved targets tracking algorithm based on Kalman filter and Particle filter was proposed.Firstly,a candidate object was gotten by Kalman tracking algorithm.Then,the tracking result would be verified by Particle filter algorithm when the match threshold is lower than a certain.The improved algorithm used template buffer to up...
Keywords:Kalman filter  particle filter  object tracking  template updata  
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