Object detection based on combination of local and spatial information

被引：1

作者：

Xiao, Qinkun ^{[1
]}

Zhang, Nan ^{[1
]}

Li, Fei ^{[2
]}

Gao, Yue ^{[3
]}

机构：

[1] Xian Technol Univ, Sch Elect & Informat Engn, Xian 710032, Peoples R China

[2] Fujitsu Res & Dev Ctr Co LTD, Beijing 100025, Peoples R China

[3] Tsinghua Univ, Dept Automat, Beijing 100084, Peoples R China

来源：

JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS | 2011年 / 22卷 / 04期

基金：

中国国家自然科学基金;

关键词：

object detection; codebook dictionary; spatial matching; local contour matching; TEXTURE;

D O I：

10.3969/j.issn.1004-4132.2011.04.023

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A method of object detection based on combination of local and spatial information is proposed. Firstly, the category-given representative images are chosen through clustering to be templates, and the local and spatial information of template are extracted and generalized as the template feature. At the same time, the codebook dictionary of local contour is also built up. Secondly, based on the codebook dictionary, sliding-window mechanism and the vote algorithm are used to select initial candidate object windows. Lastly, the final object windows are got from initial candidate windows based on local and spatial structure feature matching. Experimental results demonstrate that the proposed approach is able to consistently identify and accurately detect the objects with better performance than the existing methods.

引用

页码：715 / 720

页数：6

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