计算机应用与软件2011，Vol.28Issue(6)：47-50,120,5.
基于SIFT特征度量的Mean Shift目标跟踪算法
MEAN SHIFT OBJECT TRACKING ALGORITHM BASED ON SIFT DESCRIPTOR
摘要
Abstract
When the intricate conditions, such as scale modification, rotation, noise interference and so on, occur to the tracking object,ordinary object tracking method based on Mean Shift is difficult to get accurate tracking result. This paper proposes a feature description SIlTbased Mean Shift algorithm. It first calculates the position and scale of key points around the tracking object using SliT descriptor, as well as gets feature vectors of neighbourhood of the key point in the scale space, and then uses the histogram of module value-direction distribution of the feature vectors within the region of tracing object to delegate the moving object, at last it uses Mean Shift algorithm to track the object.Experiments results demonstrate that this algorithm can track the object accurately in conditions of scale modifications, rotation, noise interference and occlusion occurring to the tracking object with good robustness.关键词
SIFT/Mean Shift/SIFT-Mean Shift/目标跟踪Key words
Scaleinvariant feature transform (SIFT)/ Mean Shift/ SIFT-Mean Shift/ Object track引用本文复制引用
翟海涛,吴健,陈建明,崔志明..基于SIFT特征度量的Mean Shift目标跟踪算法[J].计算机应用与软件,2011,28(6):47-50,120,5.基金项目
国家自然科学基金项目(60970015) （60970015）
2008年江苏省重大科技支撑与自主创新项目(BE2008044) （BE2008044）
2009年江苏省省级现代服务业(软件产业)发展专项引导资金项目([2009]332-64) （软件产业）
苏州市应用基础研究(工业)项目(SYJG0927) （工业）
苏州大学科研预研基金. （）
