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A comparative study of existing metrics ...
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Document type :
Article dans une revue scientifique
DOI :
10.1007/s00371-010-0494-2
Title :
A comparative study of existing metrics for 3D-mesh segmentation evaluation
Author(s) :
Benhabiles, Halim [Auteur]
FOX MIIRE [LIFL]
Vandeborre, Jean-Philippe [Auteur] refId
FOX MIIRE [LIFL]
Lavoué, Guillaume [Auteur]
Geometry Processing and Constrained Optimization [M2DisCo]
Daoudi, Mohamed [Auteur]
FOX MIIRE [LIFL]
Journal title :
The Visual Computer
Pages :
1451-1466
Publisher :
Springer Verlag
Publication date :
2010-12
ISSN :
0178-2789
English keyword(s) :
3D-mesh segmentation
ground-truth
similarity metric
subjective tests
evaluation
HAL domain(s) :
Informatique [cs]/Vision par ordinateur et reconnaissance de formes [cs.CV]
Informatique [cs]/Multimédia [cs.MM]
English abstract : [en]
In this paper, we present an extensive experimental comparison of existing similarity metrics addressing the quality assessment problem of mesh seg- mentation. We introduce a new metric named the 3D Normalized Probabilistic ...
Show more >
In this paper, we present an extensive experimental comparison of existing similarity metrics addressing the quality assessment problem of mesh seg- mentation. We introduce a new metric named the 3D Normalized Probabilistic Rand Index (3D-NPRI) which outperforms the others in terms of properties and discriminative power. This comparative study includes a subjective experiment with human observers and is based on a corpus of manually segmented models. This corpus is an improved version of our previous one. It is composed of a set of 3D-mesh models grouped in different classes associated with several manual ground-truth segmentations. Finally the 3D-NPRI is applied to evaluate six recent segmentation algorithms using our corpus and the Chen's et al. corpus.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
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