Titre :

Monocular 3D Reconstruction and Augmentation of Elastic Surfaces with Self-occlusion Handling

Auteur(s) :

Haouchine, Nazim [Auteur]
Computational Anatomy and Simulation for Medicine [MIMESIS]
Dequidt, Jeremie [Auteur]
Université de Lille, Sciences et Technologies
Deformable Robots Simulation Team [DEFROST ]
Berger, Marie-Odile [Auteur]
Visual Augmentation of Complex Environments [MAGRIT]
Cotin, Stephane [Auteur]
Computational Anatomy and Simulation for Medicine [MIMESIS]

Titre de la revue :

IEEE Transactions on Visualization and Computer Graphics

Pagination :

14

Éditeur :

Institute of Electrical and Electronics Engineers

Date de publication :

2015

ISSN :

1077-2626

Mot(s)-clé(s) en anglais :

Elastic Augmented Reality
Non-rigid Registration
Computer Assisted Surgery
Index Terms—Image-guided Simulation
Physics-based Modeling

Discipline(s) HAL :

Informatique [cs]

Résumé en anglais : [en]

This paper focuses on the 3D shape recovery and augmented reality on elastic objects with self-occlusions handling, using only single view images. Shape recovery from a monocular video sequence is an underconstrained problem ...
Lire la suite >This paper focuses on the 3D shape recovery and augmented reality on elastic objects with self-occlusions handling, using only single view images. Shape recovery from a monocular video sequence is an underconstrained problem and many approaches have been proposed to enforce constraints and resolve the ambiguities. State-of-the art solutions enforce smoothness or geometric constraints, consider specific deformation properties such as inextensibility or resort to shading constraints. However, few of them can handle properly large elastic deformations. We propose in this paper a real-time method that uses a mechanical model and able to handle highly elastic objects. The problem is formulated as an energy minimization problem accounting for a non-linear elastic model constrained by external image points acquired from a monocular camera. This method prevents us from formulating restrictive assumptions and specific constraint terms in the minimization. In addition, we propose to handle self-occluded regions thanks to the ability of mechanical models to provide appropriate predictions of the shape. Our method is compared to existing techniques with experiments conducted on computer-generated and real data that show the effectiveness of recovering and augmenting 3D elastic objects. Additionally, experiments in the context of minimally invasive liver surgery are also provided and results on deformations with the presence of self-occlusions are exposed.Lire moins >

Langue :

Anglais

Comité de lecture :

Oui

Audience :

Internationale

Vulgarisation :

Non

Collections :

• Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189

Source :

Harvested from HAL