Abstract
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.
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This work is supported by National Science Foundation of China under Grant No. 61001165, Heilongjiang Provincial Natural Science Foundation of China under Grant No. QC2010066, and HIT Young Scholar Foundation of 985 Project.
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Li, JB., Sun, WH., Wang, YH. et al. 3D model classification based on nonparametric discriminant analysis with kernels. Neural Comput & Applic 22, 771–781 (2013). https://doi.org/10.1007/s00521-011-0768-2
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DOI: https://doi.org/10.1007/s00521-011-0768-2