3D Markerless Human Limb Localization through Robust Energy Minimization

Abstract : Markerless human tracking addresses the problem of estimating human body motion in non-cooperative environments. Computer Vision techniques combined with Pattern Recognition theory serve the purpose of extracting information on human body postures from video-sequences, without the need of wearable markers. Multi-camera systems further enhance this kind of application providing frames from multiple viewpoints. This work tackles the application of multi-camera posture estimation through the use of a multi-camera environment, also known as "smart space". A 3D skeleton structure and geometrical descriptors of human muscles are fitted to the volumetric data to directly recover 3D information. 3D skeleton deformations and bio-mechanical constraints on joint models are used to provide posture information at each frame. The proposed system does not require any pre-initialization phase and automatically adapt the skeleton and the volumetric occupation of each limb to the actor physiognomy independently from the pose. Exhaustive tests were performed to validate our approach.
Type de document :
Communication dans un congrès
Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008
Liste complète des métadonnées

Littérature citée [15 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/inria-00326757
Contributeur : Peter Sturm <>
Soumis le : dimanche 5 octobre 2008 - 14:02:37
Dernière modification le : lundi 6 octobre 2008 - 09:27:43
Document(s) archivé(s) le : lundi 8 octobre 2012 - 13:57:45

Fichier

1569140040.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

  • HAL Id : inria-00326757, version 1

Collections

Citation

Marco Marcon, Massimiliano Pierobon, Augusto Sarti, Stefano Tubaro. 3D Markerless Human Limb Localization through Robust Energy Minimization. Workshop on Multi-camera and Multi-modal Sensor Fusion Algorithms and Applications - M2SFA2 2008, Oct 2008, Marseille, France. 2008. 〈inria-00326757〉

Partager

Métriques

Consultations de la notice

139

Téléchargements de fichiers

170