[en] In this paper, we target enhanced 3D reconstruction of non-rigidly
deforming objects based on a view-independent surface representation with an
automated recursive filtering scheme. This work improves upon the KinectDeform
algorithm which we recently proposed. KinectDeform uses an implicit viewdependent
volumetric truncated signed distance function (TSDF) based surface
representation. The view-dependence makes its pipeline complex by requiring
surface prediction and extraction steps based on camera’s field of view. This paper
proposes to use an explicit projection-based Moving Least Squares (MLS)
surface representation from point-sets. Moreover, the empirical weighted filtering
scheme in KinectDeform is replaced by an automated fusion scheme based
on a Kalman filter. We analyze the performance of the proposed algorithm both
qualitatively and quantitatively and show that it is able to produce enhanced and
feature preserving 3D reconstructions.
Centre de recherche :
SnT, Interdisciplinary Centre for Security, Reliability and Trust
Disciplines :
Sciences informatiques
Auteur, co-auteur :
AFZAL, Hassan ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
AOUADA, Djamila ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Destelle, Francois; Dublin City University, Ireland > Insight: Centre for Data Analytics
Mirbach, Bruno
OTTERSTEN, Björn ; University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT)
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
View-Independent Enhanced 3D Reconstruction of Non-Rigidly Deforming Objects
Date de publication/diffusion :
2015
Nom de la manifestation :
16th International Conference on Computer Analysis of Images and Patterns
Date de la manifestation :
from 02-09-2015 to 04-09-2015
Manifestation à portée :
International
Titre de l'ouvrage principal :
16th International Conference on Computer Analysis of Images and Patterns
