Object Recognition Based on Three-Dimensional Model

被引：0

作者：

Liang, Jun ^{[1
]}

Zhang, Yanning ^{[1
]}

Lin, Zenggang ^{[1
]}

Guo, Zhe ^{[1
]}

Zhang, Chao ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Comp Sci, Shaanxi Prov Key Lab Speech & Image Informat Proc, Xian 710072, Peoples R China

来源：

INTELLIGENT SCIENCE AND INTELLIGENT DATA ENGINEERING, ISCIDE 2011 | 2012年 / 7202卷

关键词：

Object recognition; 3D model; multiple view feature model; normalized Fourier Descriptor; SVM; SUPPORT VECTOR MACHINES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

It is a challenging work to achieve viewpoint independent object recognition. A new efficient method of object recognition based on 3D model is proposed in this paper. Firstly, we obtain multiple 2D projected images of a single 3D model from different directions, and then extract the normalized Fourier Descriptors of the object's edge in the projected images. According to the fact that 2D projection images within limited view range have continuity and similarity, projections can be clustered into the multiple view feature model, leading to an appropriate number of cluster classes and increases the recognition rate. Finally, the SVM classifier is used for recognition. The experiment results show the effectiveness and efficiency of method proposed.

引用

页码：218 / 225

页数：8

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