1. A spectral graph wavelet approach for nonrigid 3D shape retrieval.
- Author
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Masoumi, Majid, Li, Chunyuan, and Ben Hamza, A.
- Subjects
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SHAPE recognition (Computer vision) , *WAVELET transforms , *FEATURE selection , *DESCRIPTOR systems , *IMAGE retrieval , *COMPUTER science - Abstract
In this paper, we propose a spectral graph wavelet approach for 3D shape retrieval using the bag-of-features paradigm. In an effort to capture both local and global characteristics of a 3D shape, we present a three-step feature description framework. Local descriptors are first extracted via the spectral graph wavelet transform having the Mexican hat wavelet as a generating kernel. Then, mid-level features are obtained by embedding local descriptors into the visual vocabulary space using the soft-assignment coding step of the bag-of-features model. A global descriptor is subsequently constructed by aggregating mid-level features weighted by a geodesic exponential kernel, resulting in a matrix representation that describes the frequency of appearance of nearby codewords in the vocabulary. Then, we compare the global descriptor of a query to all global descriptors of the shapes in the dataset using a dissimilarity measure and find the closest shape. Experimental results on two standard 3D shape benchmarks demonstrate the effectiveness of the proposed shape retrieval approach in comparison with state-of-the-art methods. [ABSTRACT FROM AUTHOR]
- Published
- 2016
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