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基于多尺度特征提取的Kalman滤波跟踪
引用本文:孔军,汤心溢,蒋敏,刘士建,李丹.基于多尺度特征提取的Kalman滤波跟踪[J].红外与毫米波学报,2011,30(5):446-450.
作者姓名:孔军  汤心溢  蒋敏  刘士建  李丹
作者单位:1. 江南大学物联网工程学院,江苏无锡214122;中国科学院上海技术物理研究所,上海200083;中国科学院研究生院,北京100049
2. 中国科学院上海技术物理研究所,上海,200083
3. 江南大学物联网工程学院,江苏无锡,214122
4. 中国科学院上海技术物理研究所,上海200083;中国科学院研究生院,北京100049
基金项目:国家自然科学基金项目(面上项目,重点项目,重大项目)
摘    要:针对波动性较大目标跟踪,传统Kalman滤波算法鲁棒性和实时性不足,提出一种基于多尺度特征提取的Kalman跟踪算法.前帧目标区域特征点匹配出后续帧目标区域特征点,并以后者特征点为中心,建立搜索区域,避免了遍历整幅后续帧图像,快速地为Kalman滤波方程状态后验值提供了稳定的观测信号和观测残差.实验证明,这种作为约束条...

关 键 词:目标跟踪  多尺度特征提取  Kalman滤波  收敛
收稿时间:2010/12/1 0:00:00
修稿时间:2010/12/22 0:00:00

Target tracking based on multi-scale feature extraction Kalman filter
KONG Jun,TANG Xin-Yi,JIANG Min,LIU Shi-Jian and LI Dan.Target tracking based on multi-scale feature extraction Kalman filter[J].Journal of Infrared and Millimeter Waves,2011,30(5):446-450.
Authors:KONG Jun  TANG Xin-Yi  JIANG Min  LIU Shi-Jian and LI Dan
Affiliation:Shanghai Institute of Technical Physics, Chinese Academy of Sciences,Shanghai Institute of Technical Physics, Chinese Academy of Sciences,School of Internet of Things and Sensor Network Engineering, Jiangnan University,Shanghai Institute of Technical Physics, Chinese Academy of Sciences and Shanghai Institute of Technical Physics, Chinese Academy of Sciences
Abstract:To overcome the deficiency of the robustness and real-time performance of traditional Kalman filter used for changeable target tracking, a new Kalman algorithm based on multi-scale feature extraction was proposed. After the feature points of a frame matched ones of the follow-up frame in the target area of image, the latter feature points centroid was took as the center from which the searching area was located so as to avoid traversing the whole image. So the stable signals and residuals of observations were provided to the Kalman filter equations to calculate accurately the posteriori state value. Experiment show that the multi-scale feature extraction technology introduced into the traditional Kalman filter equation as constrained conditions reduced filtering time and restrained divergence. Thus improved filter has good convergence.
Keywords:target tracking  multi-scale feature extraction  Kalman filter  convergence
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