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Salient Local 3D Features for 3D Shape Retrieval

Published

Author(s)

Afzal A. Godil, Asim Wagan

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.
Proceedings Title
SPIE Symposium Electronic Imaging
Conference Dates
January 23-27, 2011
Conference Location
San Francisco , CA
Conference Title
IS&T / SPIE 3D Image Processing and Applications

Keywords

3D model retrieval, voxel grid, non-rigid 3D Model retrieval, bag of words approach, Scale Invariant Feature Transform (SIFT)

Citation

Godil, A. and Wagan, A. (2011), Salient Local 3D Features for 3D Shape Retrieval, SPIE Symposium Electronic Imaging , San Francisco , CA (Accessed June 18, 2024)

Issues

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Created April 7, 2011, Updated February 19, 2017