计算机工程与应用Issue(22)：193-198,6.DOI:10.3778/j.issn.1002-8331.1310-0297
基于改进的颜色和SURF特征的粒子滤波目标跟踪
Targets tracking based on improved color histogram and SURF features using particle filter
摘要
Abstract
In order to track moving targets of video exactly, a novel tracking scheme is proposed using particle filter based on improved color histogram features and Speeded Up Robust Features(SURF). SURF algorithm is applied to extracting features. The features are tracked stably by the hierarchically iterative matching of the Kanade-Lucas-Tomasi(KLT) matching algorithm. Based on fusion mode of multiplicative weights, the SURF and improved saliency weighted color histo-gram are used to the joint observation probability. Meanwhile, for avoiding the drop of SURF matching numbers and the instability in tracking process, a SURF feature-point-set update method is presented. Through using multi-group experiments, the results demonstrate that this approach has great robustness for either sunlight or block and has high accuracy in tracking.关键词
目标跟踪/视觉显著性/颜色直方图/加速鲁棒特征(SURF)/粒子滤波/KLT算法Key words
target tracking/visual saliency/color histogram/Speeded Up Robust Features(SURF)/particle filter/KLT algorithm分类
信息技术与安全科学引用本文复制引用
金志刚,卫津津,罗咏梅,刘晓辉..基于改进的颜色和SURF特征的粒子滤波目标跟踪[J].计算机工程与应用,2015,(22):193-198,6.基金项目
国家高技术研究发展计划（863）（No.2009AA01A336）。 （）
