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Front. Inform. Technol. Electron. Eng.  2013, Vol. 14 Issue (7): 551-560    DOI: 10.1631/jzus.CIDE1308
    
Extracting 3D model feature lines based on conditional random fields
Yao-ye Zhang, Zheng-xing Sun, Kai Liu, Mo-fei Song, Fei-qian Zhang
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China
Extracting 3D model feature lines based on conditional random fields
Yao-ye Zhang, Zheng-xing Sun, Kai Liu, Mo-fei Song, Fei-qian Zhang
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210046, China
 全文: PDF 
摘要： We propose a 3D model feature line extraction method using templates for guidance. The 3D model is first projected into a depth map, and a set of candidate feature points are extracted. Then, a conditional random fields (CRF) model is established to match the sketch points and the candidate feature points. Using sketch strokes, the candidate feature points can then be connected to obtain the feature lines, and using a CRF-matching model, the 2D image shape similarity features and 3D model geometric features can be effectively integrated. Finally, a relational metric based on shape and topological similarity is proposed to evaluate the matching results, and an iterative matching process is applied to obtain the globally optimized model feature lines. Experimental results showed that the proposed method can extract sound 3D model feature lines which correspond to the initial sketch template.
关键词： Nonphotorealistic rendering;  Model feature lines;  Conditional random fields;  Feature line metrics;  Iterative matching    
Abstract: We propose a 3D model feature line extraction method using templates for guidance. The 3D model is first projected into a depth map, and a set of candidate feature points are extracted. Then, a conditional random fields (CRF) model is established to match the sketch points and the candidate feature points. Using sketch strokes, the candidate feature points can then be connected to obtain the feature lines, and using a CRF-matching model, the 2D image shape similarity features and 3D model geometric features can be effectively integrated. Finally, a relational metric based on shape and topological similarity is proposed to evaluate the matching results, and an iterative matching process is applied to obtain the globally optimized model feature lines. Experimental results showed that the proposed method can extract sound 3D model feature lines which correspond to the initial sketch template.
Key words: Nonphotorealistic rendering    Model feature lines    Conditional random fields    Feature line metrics    Iterative matching
收稿日期: 2012-12-29 出版日期: 2013-07-05
CLC:  TP391  
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Yao-ye Zhang
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引用本文:

Yao-ye Zhang, Zheng-xing Sun, Kai Liu, Mo-fei Song, Fei-qian Zhang. Extracting 3D model feature lines based on conditional random fields. Front. Inform. Technol. Electron. Eng., 2013, 14(7): 551-560.

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http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.CIDE1308    或    http://www.zjujournals.com/xueshu/fitee/CN/Y2013/V14/I7/551

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