现代电子技术2018，Vol.41Issue(2)：21-25,5.DOI:10.16652/j.issn.1004-373x.2018.02.006
基于相关滤波的目标快速跟踪算法研究
Research on target fast tracking algorithm based on correlation filtering
摘要
Abstract
Correlation filtering is a very good choice to achieve fast target tracking with high accuracy,but currently all the correlation filtering tracking methods are still unable to eliminate the interference caused by factors such as occlusion and illumi-nation change. Therefore,a fast target tracking method using the multi-feature graph kernel correlation filter(MKCF)is pro-posed on the basis of the traditional kernel correlation filter(KCF). First,multiple feature graphs are generated by initializing the target area,and the location and scale KCF are obtained by means of studying the regularized least squares classifier. Second,a feature graph is randomly selected to look for the maximum output response value for the position and scale KCF, and complete the location and scale detection of the target. Finally,the target model that needs to be updated on line is random-ly selected. The experiment was carried out. Compared with KCF,the average center location error(CLE)of MKCF reduces 5 pixels,the average success rate(SR)is increased by 10.9%,and the average distance accuracy is increased by 6.7%. MKCF has strong adaptability in complex conditions when the scale,illumination and form changes,as well as target occlusion,slight rotation and fast motion occur. It has important value in theory and application research.关键词
视觉目标跟踪/相关滤波器/多特征图/平均成功率/分类器/中心位置误差Key words
visual target tracking/correlation filter/multi-feature graph/average success rate/classifier/center location error分类
信息技术与安全科学引用本文复制引用
林海涛,钟海俊,王斌,窦高奇..基于相关滤波的目标快速跟踪算法研究[J].现代电子技术,2018,41(2):21-25,5.基金项目
国家自然科学基金青年项目:基于叠加训练序列的时变信道估计及预编码信号分离策略研究(61302099)Youth Project Supported by National Natural Science Foundation of China:Research on Time-Varying Channels′ Estimation Based on Overlapping Training Sequences and Pre-coded Signals′ Separation Strategy(61302099) （61302099）
