Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
SMI '04 Proceedings of the Shape Modeling International 2004
A survey of content based 3D shape retrieval methods
Multimedia Tools and Applications
A 3D model retrieval approach using the interior and exterior 3D shape information
Multimedia Tools and Applications
3D Model Retrieval Using Probability Density-Based Shape Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Three-dimensional shape searching: state-of-the-art review and future trends
Computer-Aided Design
3D CAD model matching from 2D local invariant features
Computers in Industry
PCA-SIFT: a more distinctive representation for local image descriptors
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Efficient 3-D model search and retrieval using generalized 3-D radon transforms
IEEE Transactions on Multimedia
3D object retrieval using an efficient and compact hybrid shape descriptor
EG 3DOR'08 Proceedings of the 1st Eurographics conference on 3D Object Retrieval
Hi-index | 0.00 |
In this paper, we propose a novel hybrid shape descriptor that combines the 2D view and transform-based features. The 2D view features are extracted from six orthogonal directions of a 3D model by using the Scale Invariant Feature Transform (SIFT) method. In order to capture the six orthogonal 2D views, Continuous Principal Component Analysis (CPCA) is used to implement pose alignment. Meanwhile, the eigenspace is computed and stored to reduce the 2D view feature vector dimension. Then, the radial integral transform and the spherical integration transform are used to extract transform-based features. The similarity between the query model and models in the database is computed by using the weighted sum of 2D view and transform-based feature similarity. Experimental results show that the proposed hybrid shape descriptor can achieve satisfactory retrieval performance for both the articulated models in the McGill Shape Benchmark and the rigid models in the Princeton Shape Benchmark.