华侨大学学报（自然科学版）2018，Vol.39Issue(4)：611-617,7.DOI:10.11830/ISSN.1000-5013.201608031
抗遮挡的相关滤波目标跟踪算法
Anti-Occlusion Object Tracking Algorithm Based on Kernelized Correlation Filters
摘要
Abstract
In order to solve the problem of wrong judgment of occlusion based on traditional kernelized corre-lation filters object tracking algorithm.An anti-occlusion object tracking algorithm based on kernelized correla-tion filters is proposed.Firstly,based on the framework of kernelized correlation filters,the object position is obtained by the regularized least-squares classifiers.Secondly,a multi-scale filter is introduced and scale esti-mation is obtained through calculating the maximum value response of the multi-scale filter.Finally,in terms of the target model updating,according to the difference of target position confidence map peak sharpness,the model can correctly updated.The experimental results demonstrate that the median center location error of the proposed algorithm is 6.18 px,the average distance precision is 97.68% when the threshold is set 20 px,and the average tracking speed is 30.8 frames·s-1.The proposed algorithm can not only effectively solve target scale changes,complete occlusion and other issues in the complex background,but also has higher tracking ro-bustness and accuracy.关键词
目标跟踪/核相关滤波器/多尺度滤波器/目标模型更新Key words
target tracking/kernelized correlation filters/multi-scale filter/target model update分类
信息技术与安全科学引用本文复制引用
顾培婷,黄德天,黄炜钦,柳培忠..抗遮挡的相关滤波目标跟踪算法[J].华侨大学学报（自然科学版）,2018,39(4):611-617,7.基金项目
国家自然科学基金资助项目(61203242) （61203242）
华侨大学科研基金资助项目(13BS416) （13BS416）
