液晶与显示2016，Vol.31Issue(12)：1143-1148,6.DOI:10.3788/YJYXS20163112.1143
结合自适应核函数的 Mean-shift 改进算法
Improved mean-shift algorithm combined with adaptive kernel function
赵云峰1
作者信息
- 1. 中国人民解放军 91245 部队，辽宁 葫芦岛 125000
- 折叠
摘要
Abstract
In order to solve the problem of Mean-shift algorithm caused by the fixed track window,an improved Mean-shift algorithm using adaptive kernel function is proposed.Visual saliency weighted by the gray similarity is detected to ascertain the object area,and the adaptive kernel function is designed to track object combined with Epanechnikov and the object area,reducing the effect of fixed track window and background pixels.After plenty of experiments,the results show that the proposed method can track object scale motions in real time and exactly,and cost less than 25 ms for every frame.关键词
自适应核函数/Mean-shift/视觉显著性Key words
adaptive kernel function/Mean-shift/visual saliency分类
信息技术与安全科学引用本文复制引用
赵云峰..结合自适应核函数的 Mean-shift 改进算法[J].液晶与显示,2016,31(12):1143-1148,6.
