Estimation of Human Body Shape in Motion with Wide Clothing

Jinlong Yang 1 Jean-Sébastien Franco 1 Franck Hétroy-Wheeler 1 Stefanie Wuhrer 1
1 MORPHEO - Capture and Analysis of Shapes in Motion
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : Estimating 3D human body shape in motion from a sequence of unstructured oriented 3D point clouds is important for many applications. We propose the first automatic method to solve this problem that works in the presence of loose clothing. The problem is formulated as an optimization problem that solves for identity and posture parameters in a shape space capturing likely body shape variations. The automation is achieved by leveraging a recent robust pose detection method [1]. To account for clothing, we take advantage of motion cues by encouraging the estimated body shape to be inside the observations. The method is evaluated on a new benchmark containing different subjects, motions, and clothing styles that allows to quantitatively measure the accuracy of body shape estimates. Furthermore, we compare our results to existing methods that require manual input and demonstrate that results of similar visual quality can be obtained.
Type de document :
Communication dans un congrès
ECCV 2016 - European Conference on Computer Vision, Oct 2016, Amsterdam, Netherlands
Liste complète des métadonnées


https://hal.inria.fr/hal-01344795
Contributeur : Stefanie Wuhrer <>
Soumis le : mercredi 27 juillet 2016 - 15:20:12
Dernière modification le : vendredi 2 septembre 2016 - 08:11:22

Licence


Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale - Pas de modification 4.0 International License

Identifiants

  • HAL Id : hal-01344795, version 2

Citation

Jinlong Yang, Jean-Sébastien Franco, Franck Hétroy-Wheeler, Stefanie Wuhrer. Estimation of Human Body Shape in Motion with Wide Clothing. ECCV 2016 - European Conference on Computer Vision, Oct 2016, Amsterdam, Netherlands. 〈hal-01344795v2〉

Partager

Métriques

Consultations de
la notice

134

Téléchargements du document

203