An Efficient Volumetric Framework for Shape Tracking - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2015

An Efficient Volumetric Framework for Shape Tracking

Benjamin Allain
Edmond Boyer

Résumé

Recovering 3D shape motion using visual information is an important problem with many applications in computer vision and computer graphics, among other domains. Most existing approaches rely on surface-based strategies, where surface models are fit to visual surface observations. While numerically plausible, this paradigm ignores the fact that the observed surfaces often delimit volumetric shapes, for which deformations are constrained by the volume inside the shape. Consequently, surface-based strategies can fail when the observations define several feasible surfaces, whereas volumetric considerations are more restrictive with respect to the admissible solutions. In this work, we investigate a novel volumetric shape parametrization to track shapes over temporal sequences. In constrast to Eulerian grid discretizations of the observation space, such as voxels, we consider general shape tesselations yielding more convenient cell decompositions, in particular the Centroidal Voronoi Tesselation. With this shape representation, we devise a tracking method that exploits volumetric information, both for the data term evaluating observation conformity, and for expressing deformation constraints that enforce prior assumptions on motion. Experiments on several datasets demonstrate similar or improved precisions over state-of-the-art methods, as well as improved robustness, a critical issue when tracking sequentially over time frames.
Fichier principal
Vignette du fichier
1399.pdf (4 Mo) Télécharger le fichier
Vignette du fichier
thumbnailCVPR2015_250px.jpg (6.99 Ko) Télécharger le fichier
Allain_CVPR2015_Volumetric_Tracking.avi (58.36 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Format : Figure, Image
Origine : Fichiers produits par l'(les) auteur(s)
Format : Vidéo
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01141207 , version 1 (02-07-2015)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Benjamin Allain, Jean-Sébastien Franco, Edmond Boyer. An Efficient Volumetric Framework for Shape Tracking. CVPR 2015 - IEEE International Conference on Computer Vision and Pattern Recognition, Jun 2015, Boston, United States. pp.268-276, ⟨10.1109/CVPR.2015.7298623⟩. ⟨hal-01141207⟩
1157 Consultations
1140 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More