计算机技术与发展2018，Vol.28Issue(4)：60-64,70,6.DOI:10.3969/j.issn.1673-629X.2018.04.013
局部加权距离度量的双向稀疏表示目标跟踪
Target Tracking of Bidirectional Sparse Representation of Local Weighted Distance Metric
摘要
Abstract
We first propose a framework about target tracking model based on bidirectional sparse representation,which uses the L1mini-mization to constrain the forward and reverse reconstruction errors.The positive and negative sparse coefficient matrices are obtained by the algorithm of accelerated approximation gradient(APG).In this paper,we obtain the weight matrix according to the distance between the positive and negative template set and the candidate template set.By using the weight matrix and the positive and negative sparse coef-ficient matrix,the candidate samples with the largest positive and negative difference between the candidate samples are obtained,of which the optimal candidate samples are selected as the tracking optimal target.And then on the distance between the target template set and the candidate sample set,because the traditional Euclidean distance is inaccurate in the case of occlusion and illumination of the target,we propose an improved local weight distance measurement method.Compared with the traditional target tracking algorithm,the proposed al-gorithm has high robustness in the complex environment video sequence.关键词
视觉跟踪/双向稀疏/L1范数/加速逼近梯度/局部权重距离度量Key words
visual tracking/bidirectional sparse/L1-norm/accelerating approximation gradient/locally weighted distance metric分类
信息技术与安全科学引用本文复制引用
王业祥,朱文球,孙文静..局部加权距离度量的双向稀疏表示目标跟踪[J].计算机技术与发展,2018,28(4):60-64,70,6.基金项目
湖南省重点研发计划项目(2016RS2020) （2016RS2020）
