Conference paper
Statistical spherical wavelet moments for Content-based 3D model retrieval
25th Computer Graphics International Conference (CGI) 2007 (Petropolis, Brazil, 30/05/2007–02/06/2007)
2007
Abstract
The description of 3D shapes with features that are invariant under similarity transformations is one of the challenging issues in content-based 3D model retrieval. In this paper we show that shape sampling affects significantly the rotation invariance of existing shape descriptors. Then we propose a new parameterization method that samples uniformly the shape which is then fed to a spherical wavelet analyzer to extract discriminative features. We introduce new shape descriptors based on higher order statistical moments of the sphericalwavelet sub-bands of the spherical shape function. The proposed descriptors are compact and invariant under similarity transformations.We demonstrate their efficiency, using the Princeton Shape Benchmark, regarding the computational aspects and retrieval performance.
Details
- Title
- Statistical spherical wavelet moments for Content-based 3D model retrieval
- Authors/Creators
- H. Laga (Author/Creator)M. Nakajima (Author/Creator)
- Conference
- 25th Computer Graphics International Conference (CGI) 2007 (Petropolis, Brazil, 30/05/2007–02/06/2007)
- Identifiers
- 991005542887307891
- Murdoch Affiliation
- Murdoch University
- Language
- English
- Resource Type
- Conference paper
Metrics
69 File views/ downloads
45 Record Views