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基于奇异值分解的图像匹配和目标跟踪研究
引用本文:史泽林,张志佳,黄莎白. 基于奇异值分解的图像匹配和目标跟踪研究[J]. 小型微型计算机系统, 2005, 26(9): 1643-1646
作者姓名:史泽林  张志佳  黄莎白
作者单位:1. 中国科学院,沈阳自动化研究所,辽宁,沈阳,110016;中国科学院,研究生院,北京,100039
2. 中国科学院,沈阳自动化研究所,辽宁,沈阳,110016
基金项目:中国科学院科技创新基金项目(A010416)资助.
摘    要:在目标跟踪过程中,由于存在目标姿态变化和背景干扰,在跟踪过程中必须要对模板进行必要的修正,应该在获取目标模板后有一个可靠的模板更新策略.本文探讨了奇异值分解及其在图像匹配和目标跟踪中的应用,定义了一种近似奇异值向量并提出了一种基于图像奇异值特征向量数据特点的跟踪策略并作了大量试验,试验结果表明所提出的图像匹配方法和目标跟踪策略的有效性.

关 键 词:图像匹配 目标跟踪 模板更新 奇异值分解
文章编号:1000-1220(2005)09-1643-04
收稿时间:2004-03-08
修稿时间:2004-03-08

Research on Image Matching and Target Tracking Through Singular Value Decomposition
SHI Ze-lin,ZHANG Zhi-jia,HUANG Sha-bai. Research on Image Matching and Target Tracking Through Singular Value Decomposition[J]. Mini-micro Systems, 2005, 26(9): 1643-1646
Authors:SHI Ze-lin  ZHANG Zhi-jia  HUANG Sha-bai
Abstract:The paper probes into the singular value decomposition and its applications in image matching and target tracking. The singular value has robust performance that is invariant to image disturbance and it makes the proximate singular value vector defined in the paper credible to represent the image as an algebraic feature. The template image should be updated adaptively in respect that the target and background are changing during the process of target tracking. A template-updating strategy is proposed based on the characters of the singular value vector. Experiments are performed on a large test set and the results show that the proposed strategy is practical and efficient in target tracking.
Keywords:image matching   target tracking   template-updating   singular value decomposition
本文献已被 CNKI 维普 万方数据 等数据库收录!
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