A Bayesian 3-D Search Engine Using Adaptive Views Clustering

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

Type de document :

Compte-rendu et recension critique d'ouvrage

DOI :

10.1109/TMM.2006.886359

Titre :

A Bayesian 3-D Search Engine Using Adaptive Views Clustering

Auteur(s) :

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

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

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]

Titre de la revue :

IEEE Transactions on Multimedia

Pagination :

78-88

Éditeur :

Institute of Electrical and Electronics Engineers

Date de publication :

2007-01

ISSN :

1520-9210

Mot(s)-clé(s) en anglais :

Bayesian approach
clustering
3-D indexing
3-D retrieval
views

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 three-dimensional (3-D)-model indexing based on two-dimensional (2-D) views, which we call adaptive views clustering (AVC). The goal of this method is to provide an "optimal" selection ...
Lire la suite >In this paper, we propose a method for three-dimensional (3-D)-model indexing based on two-dimensional (2-D) views, which we call adaptive views clustering (AVC). The goal of this method is to provide an "optimal" selection of 2-D views from a 3-D model, and a probabilistic Bayesian method for 3-D-model retrieval from these views. The characteristic view selection algorithm is based on an adaptive clustering algorithm and uses statistical model distribution scores to select the optimal number of views. Starting from the fact that all views do not have equal importance, we also introduce a novel Bayesian approach to improve the retrieval. Finally, we present our results and compare our method to some state-of-the-art 3-D retrieval descriptors on the Princeton 3-D Shape Benchmark database and a 3-D-CAD-models database supplied by the car manufacturer Renault.Lire moins >

Langue :

Anglais

Vulgarisation :

Non

Collections :