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基于谱特征和深度信任网络的三维模型分类
Alternative Title3D Shape Classification Based on Deep Belief Network and Spectral Feature
高恩阳; 刘伟军; 王天然; 邓华波
Department装备制造技术研究室
Source Publication机械设计与制造
ISSN1001-3997
2013
Issue3Pages:250-252
Contribution Rank1
Funding Organization973项目—数学机械化方法及其在数字化设计制造中的应用(2011CB302400)
Keyword模型分类 深度信任网络 特征提取
Abstract在CAD/CAM技术中,三维模型的分类问题是重要的问题。以往的工作主要考虑刚性模型分类问题。由于存在非刚性变形,大大增加了三维模型分类问题的难度。针对非刚性三维模型分类问题进行了研究,提出了一种基于谱特征和深度信任网络的三维模型分类方法。首先,提取一个三维模型的谱特征;之后,通过深度信任网络对该模型进行降维;最后通过支持向量机进行判别分类。实验表明,提出的方法能有效地描述非刚性三维模型的内在特征,取得了较好的分类效果。
Other AbstractIn CAD/CAM,the classification of three-dimensional model is an important issue. Previous work mainly considered the classification of the rigid model. Due to the presence of non-rigid deformation,the difficulty of the three-dimensional model classification problem greatly increased. Three-dimensional model classification method based on spectral feature and depth belief network were proposed. First,spectral feature of a 3D model was extracted; then the main component in the spectral features was extracted by DBN dimensionality reduction;finally,discriminated classification by support vector machine was applied. The experiments showed that the proposed method based on spectral feature and deep belied network can effectively describe the intrinsic feature of the non-rigid three-dimensional model to obtain a better classification results.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/12454
Collection智能产线与系统研究室
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院研究生院
Recommended Citation
GB/T 7714
高恩阳,刘伟军,王天然,等. 基于谱特征和深度信任网络的三维模型分类[J]. 机械设计与制造,2013(3):250-252.
APA 高恩阳,刘伟军,王天然,&邓华波.(2013).基于谱特征和深度信任网络的三维模型分类.机械设计与制造(3),250-252.
MLA 高恩阳,et al."基于谱特征和深度信任网络的三维模型分类".机械设计与制造 .3(2013):250-252.
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