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.
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.
出处
《小型微型计算机系统》
CSCD
北大核心
2005年第9期1643-1646,共4页
Journal of Chinese Computer Systems
基金
中国科学院科技创新基金项目(A010416)资助.
关键词
图像匹配
目标跟踪
模板更新
奇异值分解
image matching
target tracking
template-updating
singular value decomposition
