3D model classification based on nonparametric discriminant analysis with kernels

被引:9
|
作者
Li, Jun-Bao [1 ]
Sun, Wen-He [2 ]
Wang, Yun-Heng [1 ,3 ]
Tang, Lin-Lin [4 ]
机构
[1] Harbin Inst Technol, Dept Automat Test & Control, Harbin 150006, Peoples R China
[2] Harbin Univ Commerce, Sch Comp & Informat Engn, Harbin, Peoples R China
[3] Heilongjiang Inst Sci & Technol, Coll Elect & Informat Engn, Harbin 150027, Heilongjiang, Peoples R China
[4] Shenzhen Grad Sch, Sch Comp Sci & Technol, Harbin Inst Technol, Shenzhen, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2013年 / 22卷 / 3-4期
基金
美国国家科学基金会;
关键词
3D model classification; Feature extraction of 3D model; Nonparametric discriminant analysis; Kernel method; SIMILARITY SEARCH;
D O I
10.1007/s00521-011-0768-2
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
3D model classification has many applications in CAD, 3D object retrieval, and so on. The description of 3D model is crucial but difficult, which leads to the difficulty of classification. The traditional classifier has its limitation in classification of 3D model description. In this paper, we present 3D model classification-based nonparametric discriminant analysis with kernels combined with geometry projection-based histogram model for invariable feature extraction. Firstly, we present nonparametric discriminant analysis with kernels, and secondly, we proposed the invariable feature extraction method with geometry projection-based histogram model. Thirdly, we present the framework of 3D model classification using the proposed nonparametric discriminant analysis with kernels and geometry projection-based histogram model. Finally, we testify the feasibility of the proposed algorithm and performance on 3D model classification. The experimental results show that the proposed scheme is feasible and effective on 3D model classification on the public datasets.
引用
收藏
页码:771 / 781
页数:11
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