计算机工程与应用2012，Vol.48Issue(34)：171-174,198,5.DOI:10.3778/j.issn.1002-8331.1105-0176
多特征自适应融合的军事伪装目标跟踪
Military camouflage target tracking based on features fusion adaptively
摘要
Abstract
When the moving object is occluded, or similar to background, it is hard to track the moving object. An optimize particle filter arithmetic based on adaptive features fusion mean shift method is proposed to solve this problem. This paper uses united histogram to describe the grayscale and gradient direction features of the object, adjusts features weight adaptively based on the features dependability of the object of prior picture. In particle filter theory it uses the improved mean-shift method to make particles of the particle filter to move towards estimated direction of maximal posterior kernel density of the target state, and designs a fusion observational model to improve the scene adaptability. The experimental result show that this algorithm can track military camouflage target reposefully where the color for both target and background are similar, and is robust for serious occlusion.关键词
目标跟踪/特征融合/均值漂移/粒子滤波Key words
object tracking/ features fusion/ mean-shift/ particle filter分类
信息技术与安全科学引用本文复制引用
李科,徐克虎,张波..多特征自适应融合的军事伪装目标跟踪[J].计算机工程与应用,2012,48(34):171-174,198,5.基金项目
国家部委重点科研项目. （）
