[1]张红梅,温荟然,张向利,等.基于压缩特征的稀疏表示运动目标跟踪[J].郑州大学学报(工学版),2016,37(03):21-26.[doi:10.13705/j.issn.1671-6833.2016.03.005]
　Zhang Hongmei,Wen Hueran,Zhang Xiangli,et al.Sparse representation tracking via compressed features[J].Journal of Zhengzhou University (Engineering Science),2016,37(03):21-26.[doi:10.13705/j.issn.1671-6833.2016.03.005]
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基于压缩特征的稀疏表示运动目标跟踪()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
37
期数:
2016年03期
页码:
21-26
栏目:
出版日期:
2016-05-10

文章信息/Info

Title:
Sparse representation tracking via compressed features
作者:
张红梅; 温荟然; 张向利; 李鹏飞
桂林电子科技大学信息与通信学院,广西桂林,541004
Author(s):
Zhang Hongmei;  Wen Hueran;  Zhang Xiangli;  Li Pengfei
School of Guilin University of Electronic Technology, Guilin, Guangxi, 541004
关键词:
特征压缩; 稀疏表示; 粒子滤波; 块正交匹配
Keywords:
features compression; sparse representation; particle filter; block orthogonal matching
分类号:
TP391
DOI:
10.13705/j.issn.1671-6833.2016.03.005
文献标志码:
A
摘要:
为了应对目标跟踪中光照、遮挡、以及自身运动等因素的影响,采用积分图方法提取目标模板的haar-like特征,用满足有限等距条件(RIP)的随机稀疏矩阵对特征投影压缩,简化目标特征字典的构建;同时,在字典中融入背景信息,利用目标与背景的简单关系提高跟踪的精度;最后,利用块正交匹配追踪(BOMP)算法进行成块重构目标,加快了对稀疏表示的求解,增强了跟踪的实时性.通过实验发现,使用基于压缩特征的块正交匹配跟踪算法(CF-BOMP)能构建一个有效的目标外观模型,增强跟踪的稳定性,提高跟踪的实时性.
Abstract:
In order to deal with the influence of the factors such as light, shade, movement of object and etc.,the integral graph method is used to extract the Haar-like features of the target template, and the features arecompressed by a random sparse matrix which meets the limited equidistant conditions( RIP), then the con-struction of the target features dictionary is simplified. Meanwhile, the background information is added in thedictionary, and the simple relationship between the target and the background is used to improve the accuracyof tracking. At last, the target can be reconstructed in block by using the block orthogonal matching pursuit(BOMP)reconstruction algorithm, through which can enhances tracking speed. The experimental results showthat, the block orthogonal matching pursuit tracking algorithm based on compression feature is powerful in val-id target appearance model construction. And it also enhances the tracking stability and improves trackingspeed.

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　ZHANG Yong,DANG Lan-xue.Sparse Representation-based Face RecognitionMethod by LDA Feature Extraction[J].Journal of Zhengzhou University (Engineering Science),2015,36(03):94.[doi:10.3969/ j.issn.1671 -6833.2015.02.021]

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