液晶与显示2017，Vol.32Issue(12)：993-998,6.DOI:10.3788/YJYXS20173212.0993
基于多模板的深度核相关滤波跟踪
Depth kernel correlation filtering tracking based on multi-template
摘要
Abstract
Aiming at the problems of occlusion,scale transformation and illumination change in the tracking process,a depth kernel correlation filtering algorithm is proposed based on the multi-template.Firstly,the multi-template algorithm selects the best filtering parameters to optimize the ability of the classifier training samples.The various features are used to optimize the target appearance model which improves the robustness of the multi-feature algorithm.Then,in the tracking process,the depth map information is applied to calculate the target overlap rate which is employed to judge whether the tracking target is occluded.When occlusion occurs,the target search area is redefined,and the target is judge whether to track gain.So it reduces the problem of algorithm drift in the case of occlusion.Finally,according to whether or not occlusion occurs,the classifier parameters and target appearance model are determined whether to update.It improves the reliability of template updates.Using the Princeton database test algorithm,the success rate and accuracy is 85.1％ and 98.6％ respectively,which is 7.04％ and 4.67％ higher than the second algorithm respectively.Experiments show that the depth kernel correlation filtering algorithm based on multi-template is superior to the traditional algorithm,and has certain research value.关键词
目标跟踪/多模板/深度信息/重叠率Key words
target tracking/multi-template/depth information/overlap分类
信息技术与安全科学引用本文复制引用
李雪晴,杨德东,毛宁,杨福才..基于多模板的深度核相关滤波跟踪[J].液晶与显示,2017,32(12):993-998,6.基金项目
国家自然科学基金项目(No.61203076) （No.61203076）
河北省自然科学基金项目(No.F2017202009)Project supported by the National Natural Science Foundation of China (No.61203076) （No.F2017202009）
Project supported by the Natural Science Foundation of Hebei,China(No.F2017202009) （No.F2017202009）
