Improved BOF Method for Person Re-identification

被引：0

作者：

Zhang, Lixia ^{[1
]}

Li, Kangshun ^{[2
]}

机构：

[1] South China Agr Univ, Coll Math & Informat, Guangzhou, Guangdong, Peoples R China

[2] South China Agr Univ, Shenzhen Suodi Statistician Co Ltd, Coll Math & Informat, Guangzhou, Guangdong, Peoples R China

来源：

PROCEEDINGS OF 2016 12TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY (CIS) | 2016年

关键词：

Person Re-identification; BOF; Space pyramid; LIBSVM; RANKING;

D O I：

10.1109/CIS.2016.115

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Feature representation and matching are two challenging problems for person e-identification problem. Designing a suitable feature representation method, and the according high efficiency matching scheme is meaningful. In this paper, a new person re-identification method was put forward. First, an improved BOF method was proposed, it use SURF algorithm to extract the preliminary feature and generate visual dictionary. And then, an effective classifier was designed by LIBSVM technology. This method can deal with illumination and scale invariants, and improve the efficiency of the matching process. The experimental results show that it is an effective scheme for person re-identification.

引用

页码：479 / 482

页数：4

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