Belief-function based framework for deformable 3D-shape retrieval - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2014

Belief-function based framework for deformable 3D-shape retrieval

Résumé

The need for efficient tools to index and retrieve 3D content becomes even more acute. This paper presents a fully automatic 3D-object retrieval method. It consists of two main steps namely shape signature extraction to describe the shape of objects, and similarity computing to compute similarity between objects. In the first step (signature extraction), we use a shape descriptor called geodesic cords. This descriptor can be seen as a probability distribution sampled from a shape function. In the second step (similarity computing), a global distance, based on belief function theory, is computed between each pairwise of descriptors corresponding respectively to an object query and an object from a given database. Experiments on commonly-used benchmarks demonstrate that our method obtains competitive performance compared to 3D-object retrieval methods from the state-of-the-art.
Fichier non déposé

Dates et versions

hal-01081977 , version 1 (12-11-2014)

Identifiants

  • HAL Id : hal-01081977 , version 1

Citer

Halim Benhabiles, Hedi Tabia, Jean-Philippe Vandeborre. Belief-function based framework for deformable 3D-shape retrieval. International Conference on Pattern Recognition, Aug 2014, Stockholm, Sweden. ⟨hal-01081977⟩
149 Consultations
0 Téléchargements

Partager

Gmail Facebook X LinkedIn More