A subjective experiment for 3D-mesh segmentation evaluation

Benhabiles, Halim; Lavoué, Guillaume; Vandeborre, Jean Philippe; Daoudi, Mohamed

Document type :

Communication dans un congrès avec actes

Title :

A subjective experiment for 3D-mesh segmentation evaluation

Author(s) :

Benhabiles, Halim [Auteur]

FOX MIIRE [LIFL]
Lavoué, Guillaume [Auteur]
Geometry Processing and Constrained Optimization [M2DisCo]
Vandeborre, Jean Philippe [Auteur correspondant]

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

Institut TELECOM/TELECOM Lille1
FOX MIIRE [LIFL]

Scientific editor(s) :

IEEE

Conference title :

IEEE International Workshop on Multimedia Signal Processing (MMSP'2010)

City :

Saint-Malo

Country :

France

Start date of the conference :

2010-10-04

Publisher :

IEEE

Publication date :

2010-10

HAL domain(s) :

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

English abstract : [en]

In this paper we present a subjective quality assessment experiment for 3D-mesh segmentation. For this end, we carefully designed a protocol with respect to several factors namely the rendering conditions, the possible ...
Show more >In this paper we present a subjective quality assessment experiment for 3D-mesh segmentation. For this end, we carefully designed a protocol with respect to several factors namely the rendering conditions, the possible interactions, the rating range, and the number of human subjects. To carry out the subjective experiment, more than 40 human observers have rated a set of 250 segmentation results issued from various algorithms. The obtained Mean Opinion Scores, which represent the human subjects' point of view toward the quality of each segmentation, have then been used to evaluate both the quality of automatic segmentation algorithms and the quality of similarity metrics used in recent mesh segmentation benchmarking systems.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

ANR Project :

3D Models And Dynamic models Representation And Segmentation

Collections :