JOURNAL ARTICLE

Salient local 3D features for 3D shape retrieval

Afzal GodilAsim Imdad Wagan

Year: 2010 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 7864 Pages: 78640S-78640S   Publisher: SPIE

Abstract

In this paper we describe a new formulation for the 3D salient local features based on the voxel grid inspired by the Scale Invariant Feature Transform (SIFT). We use it to identify the salient keypoints (invariant points) on a 3D voxelized model and calculate invariant 3D local feature descriptors at these keypoints. We then use the bag of words approach on the 3D local features to represent the 3D models for shape retrieval. The advantages of the method are that it can be applied to rigid as well as to articulated and deformable 3D models. Finally, this approach is applied for 3D Shape Retrieval on the McGill articulated shape benchmark and then the retrieval results are presented and compared to other methods.

Keywords:

Metrics

20
Cited By
0.79
FWCI (Field Weighted Citation Impact)
0
Refs
0.72
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

3D Shape Modeling and Analysis
Physical Sciences →  Engineering →  Computational Mechanics
Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Processing and 3D Reconstruction
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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