西安电子科技大学学报（自然科学版）2012，Vol.39Issue(4)：1-6,45,7.DOI:10.3969/j.issn.1001-2400.2012.04.001
一种基于多特征融合的视频目标跟踪方法
Robust video object tracking algorithm based on multi-feature fusion
摘要
Abstract
Object tracking using multiple features has poor performance under complex scenes and when occlusion occurs- Therefore, an algorithm for fusing multiple features adaptively in the particle filter tracking framework is proposed. The tracked object is represented by the fusion of all features under linear weighting, and a new method to estimate the fusion coefficient is also proposed according to the weight distribution of all particles as well as their spatial concentrations, thus improving the reliability of multi features fusion. Besides, a dynamic updating strategy is used to adjust the update speed of each feature template adaptively, thus alleviating the affection of object deformation. According to the confidence ai each feature, an occlusion handling strategy is invoked to decrease the influence of partial occlusion. Analysis and experiment show that the proposed method is more robust under complex scenes, and is applicable in the presence of occlusions.关键词
目标跟踪/多特征融合/粒子滤波/模型更新Key words
object tracking/ multi-feature fusion/ particle filter/ template update分类
信息技术与安全科学引用本文复制引用
李远征,卢朝阳,李静..一种基于多特征融合的视频目标跟踪方法[J].西安电子科技大学学报（自然科学版）,2012,39(4):1-6,45,7.基金项目
国家自然科学基金资助项目(60878141) （60878141）
中央高校基本科研业务费专项资金资助项目(K50510010007) （K50510010007）
陕西省自然科学基础研究计划资助项目(2009JQ8019) （2009JQ8019）
