3D Model Retrieval based on Adaptive Views Clustering

Filali Ansary, Tarik; Daoudi, Mohamed; Vandeborre, Jean Philippe

Type de document :

Communication dans un congrès avec actes

Titre :

3D Model Retrieval based on Adaptive Views Clustering

Auteur(s) :

Filali Ansary, Tarik [Auteur]
FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1
Daoudi, Mohamed [Auteur]

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]
Vandeborre, Jean Philippe [Auteur correspondant]

FOX MIIRE [LIFL]
Institut TELECOM/TELECOM Lille1

Titre de la manifestation scientifique :

3rd International Conference on Advances in Pattern Recognition (ICAPR 2005)

Ville :

Bath

Pays :

Royaume-Uni

Date de début de la manifestation scientifique :

2005-08-22

Titre de l’ouvrage :

3rd International Conference on Advances in Pattern Recognition (ICAPR 2005)

Date de publication :

2005-08-22

Mot(s)-clé(s) en anglais :

3D-model retrieval
indexing
bayesian probabilities

Discipline(s) HAL :

Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]

Résumé en anglais : [en]

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 ...
Lire la suite >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.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL

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