舰船电子工程2012，Vol.32Issue(10)：38-41,46,5.
基于多特征信息和直方图相交的改进Meanshift算法
Improved Mean Shift Algorithm with Multi-cue Integration and Histogram Intersection
李晖宙1
作者信息
- 1. 海军工程大学电子工程学院,武汉430033
- 折叠
摘要
Abstract
The mean shift tracker is commonly used in real-time target tracking.However,the original mean shift tracker employs only color feature and uses the Bhattacharya coefficient as similarity measure,resulting in low tracking accuracy.This paper proposed a novel tracking algorithm,which integrated color and texture features and employed histogram intersection and Powell's method to track.Firstly,texture feature was extracted by the Local Binary Pattern texture operator and integrated with color feature adaptively.Log-likelihood ratio histogram was proposed to represent objects instead of histogram.Then,the rough location of the target was obtained by the mean shift algorithm based on the two features.Finally,histogram intersection was defined as the similarity metric between the target model and candidates and iteratively maximized by Powell's method.Experimental results demonstrate the proposed method can track targets more accurately and fast.关键词
目标跟踪/Mean-Shift算法/多特征融合/直方图交集/Powell方法Key words
target tracking/Mean Shift/multi-cue integration/histogram intersection/Powell's method分类
信息技术与安全科学引用本文复制引用
李晖宙..基于多特征信息和直方图相交的改进Meanshift算法[J].舰船电子工程,2012,32(10):38-41,46,5.
