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Communication Dans Un Congrès Année : 2005

3D Model Retrieval based on Adaptive Views Clustering

Résumé

In this paper, we propose a method for 3D model indexing based on 2D views, named AVC (Adaptive Views Clustering). The goal of this method is to provide an optimal selection of 2D views from a 3D model, and a probabilistic Bayesian method for 3D model retrieval from these views. The characteristic views selection algorithm is based on an adaptive clustering algorithm and using statistical model distribution scores to select the optimal number of views. Starting from the fact that all views do not contain the same amount of information, we also introduce a novel Bayesian approach to improve the retrieval. We finally present our results and compare our method to some state of the art 3D retrieval descriptors on the Princeton 3D Shape Benchmark database.
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Dates et versions

hal-00725590 , version 1 (27-08-2012)

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  • HAL Id : hal-00725590 , version 1

Citer

Tarik Filali Ansary, Mohamed Daoudi, Jean-Philippe Vandeborre. 3D Model Retrieval based on Adaptive Views Clustering. 3rd International Conference on Advances in Pattern Recognition (ICAPR 2005), Aug 2005, Bath, United Kingdom. ⟨hal-00725590⟩
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