Temporally coherent mesh sequence segmentations

Romain Arcila; Cédric Cagniart; Franck Hétroy; Edmond Boyer; Florent Dupont

hal-00658060, version 1

Temporally coherent mesh sequence segmentations

Romain Arcila ()^a^, 1, 2, Cédric Cagniart ³, Franck Hétroy (, ) ¹, Edmond Boyer (, ) ¹, Florent Dupont () ²

N° RR-7856 (2012)

Abstract: In this report, we consider the problem of fully automatic segmentation of mesh sequences, with or without temporal coherence. More precisely, our goal is to identify model parts that consistently move rigidly over time. We propose a novel framework that incrementally adapts segments along a sequence based on the coherence of motion information within each segment. In contrast to existing approaches, this framework handles meshes independently reconstructed at each time instant, provided that motion cues are available. It allows therefore for meshes with varying connectivity as well as varying topology. Experiments on various data sets in addition to a quantitative evaluation demonstrate the effectiveness and robustness of the approach.

a – Université de Lyon
1: MORPHEO (INRIA Grenoble Rhône-Alpes / LJK Laboratoire Jean Kuntzmann)
INRIA – Institut National Polytechnique de Grenoble (INPG) – Université Joseph Fourier - Grenoble I
2: Laboratoire d'InfoRmatique en Images et Systèmes d'Information (LIRIS)
CNRS : UMR5205 – Université Claude Bernard - Lyon I – Université Lumière - Lyon II – Institut National des Sciences Appliquées (INSA) - Lyon – Ecole Centrale de Lyon
3: Computer Aided Medical Procedures & Augmented Reality (CAMPAR)
Technische Universität München (TUM)

hal-00658060, version 1
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From: Franck Hétroy <>
Submitted on: Monday, 9 January 2012 18:00:24
Updated on: Tuesday, 10 January 2012 09:24:15

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%F hal-00658060, version 1
%0 Report
%U http://hal.inria.fr/hal-00658060
%2 INFO:INFO_GR;INFO:INFO_CV
%T Temporally coherent mesh sequence segmentations
%A Arcila, Romain
%A Cagniart, Cédric
%A Hétroy, Franck
%A Boyer, Edmond
%A Dupont, Florent
%+ MORPHEO - INRIA Grenoble Rhône-Alpes / LJK Laboratoire Jean Kuntzmann , Laboratoire d'InfoRmatique en Images et Systèmes d'Information - LIRIS , Computer Aided Medical Procedures & Augmented Reality - CAMPAR
%X In this report, we consider the problem of fully automatic segmentation of mesh sequences, with or without temporal coherence. More precisely, our goal is to identify model parts that consistently move rigidly over time. We propose a novel framework that incrementally adapts segments along a sequence based on the coherence of motion information within each segment. In contrast to existing approaches, this framework handles meshes independently reconstructed at each time instant, provided that motion cues are available. It allows therefore for meshes with varying connectivity as well as varying topology. Experiments on various data sets in addition to a quantitative evaluation demonstrate the effectiveness and robustness of the approach.
%2 Nous considérons dans ce rapport le problème de la segmentation entièrement automatique de séquences de maillages, avec ou sans cohérence temporelle. Plus précisément, notre but est d'identifier les parties d'un modèle qui se déplacent rigidement de manière cohérente au cours du temps. Nous proposons un canevas nouveau pour adapter ces régions de manière incrémentale le long de la séquence, en se basant sur la cohérence de l'information de mouvement dans chaque région. Contrairement aux approches existantes, ce canevas permet de traiter les séquences de maillages reconstruits indépendamment à chaque pas de temps, pourvu que des indicateurs de mouvement soient disponibles. Il permet donc de segmenter des maillages avec changement de connectivité et/ou changement de topologie. Des expériences sur plusieurs jeux de données ainsi qu'une évaluation quantitative démontrent l'efficacité ainsi que la robustesse de cette approche.
%2 I.: Computing Methodologies/I.3: COMPUTER GRAPHICS/I.3.5: Computational Geometry and Object Modeling, I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.6: Segmentation/I.4.6.2: Region growing, partitioning, I.: Computing Methodologies/I.4: IMAGE PROCESSING AND COMPUTER VISION/I.4.8: Scene Analysis/I.4.8.2: Motion
%G English
%2 Research Report
%P 20
%8 2012-01-09
%K mesh sequence ; segmentation ; mesh tracking ; spectral clustering
%Z RR-7856
%2 4064

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