3D Model Retrieval Based on Fuzzy Correspondences and Hybrid Shape Features

2016 ◽  
Author(s):  
Liu Fu-Chang ◽  
Wang Shuang-Jian ◽  
Wang Jin-Rong ◽  
Pan Zhi-Geng ◽  
Yi Chen
Keyword(s):  
3D Model ◽  
3D Model Retrieval ◽  
Shape Features ◽  
Model Retrieval

scholarly journals AN EFFICIENT 3D MODEL RETRIEVAL BASED ON PRINCIPAL AXES ANALYSIS AND FEATURE INTEGRATION

2011 ◽  
Vol 25 (04) ◽  
pp. 583-604 ◽  
Author(s):  
SHENG-FUU LIN ◽  
CHIN-CHIA WU ◽  
CHI-YAO HSU ◽  
DOU-CHIH HSU
Keyword(s):  
3D Model ◽  
Principal Component ◽  
Zernike Moments ◽  
3D Model Retrieval ◽  
Feature Integration ◽  
Fourier Descriptors ◽  
Shape Features ◽  
Retrieval Accuracy ◽  
Principal Axes ◽  
Model Retrieval

Three-dimensional (3D) model retrieval has gathered great importance in recent years, since the number of available 3D models on the Internet has drastically increased. Many content-based 3D model retrieval approaches have been proposed. Among these methods, visual similarity-based methods have shown higher retrieval accuracy. However, because these methods capture enormous shape features from different viewpoints or locations, a large amount of calculation and comparison is necessary. Furthermore, there is a trade-off between retrieval accuracy and speed. In this paper, a 3D model retrieval method constituting Continuous Principal Component Analysis (CPCA), Fourier descriptors, and Zernike moments is proposed. CPCA is applied to extract significant shape features based on projecting the model along the principal axes. Then, Fourier descriptors and Zernike moments are used to provide shape descriptors with rotation invariants. In addition, a feature integration process combines them. A strategy of similarity measure is proposed to solve the axes switching problem. To conclude, the experimental results show that the approach outperforms SECTORS2 and D2,18 and has slightly better retrieval results than Light Field Descriptor (LFD)6 and spin-image signatures.3 Moreover, the approach is more efficient and the storage size is much less.

Projection of shape features for 3D model retrieval

2011 ◽  
Author(s):  
Chang-Hsing Lee ◽  
Jau-Ling Shih ◽  
Kun-Ming Yu ◽  
Hsiang-Yuen Chang ◽  
Yih-Chih Chiou
Keyword(s):  
3D Model ◽  
3D Model Retrieval ◽  
Shape Features ◽  
Model Retrieval

An Improved Shape Descriptor for 3D Model Retrieval

2010 ◽  
Vol 22 (5) ◽  
pp. 741-745 ◽  
Author(s):  
Xin Zhang ◽  
Rong Mo ◽  
Yuan Shi ◽  
Fangyun Zhou
Keyword(s):  
3D Model ◽  
Shape Descriptor ◽  
3D Model Retrieval ◽  
Model Retrieval

scholarly journals A novel sketch-based 3D model retrieval method by integrating skeleton graph and contour feature

2015 ◽  
Vol 9 (4) ◽  
pp. JAMDSM0049-JAMDSM0049 ◽  
Author(s):  
Haopeng LEI ◽  
Yuhua LI ◽  
Helian CHEN ◽  
Shujin LIN ◽  
Guifeng ZHENG ◽  
...  
Keyword(s):  
3D Model ◽  
3D Model Retrieval ◽  
Retrieval Method ◽  
Contour Feature ◽  
Model Retrieval ◽  
Skeleton Graph

Style-sensitive 3D model retrieval through sketch-based queries

2016 ◽  
Vol 31 (5) ◽  
pp. 2637-2644 ◽  
Author(s):  
Bin Cao ◽  
Yang Kang ◽  
Shujin Lin ◽  
Xiaonan Luo ◽  
Songhua Xu ◽  
...  
Keyword(s):  
3D Model ◽  
3D Model Retrieval ◽  
Model Retrieval
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