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MORPH-DSLAM: Model Order Reduction for Physics-Based Deformable SLAM

Article dans une revue avec comité de lecture
Author
ccBADIAS, Alberto
ALFARO, Icíar
161327 Aragón Institute of Engineering Research [Zaragoza] [I3A]
GONZALEZ, David
ccCHINESTA SORIA, Francisco
86289 Laboratoire Procédés et Ingénierie en Mécanique et Matériaux [PIMM]
ccCUETO, Elias

URI
http://hdl.handle.net/10985/23641
DOI
10.1109/tpami.2021.3118802
Date
2022-11
Journal
IEEE Transactions on Pattern Analysis and Machine Intelligence

Abstract

We propose a new methodology to estimate the 3D displacement field of deformable objects from video sequences using standard monocular cameras. We solve in real time the complete (possibly visco-)hyperelasticity problem to properly describe the strain and stress fields that are consistent with the displacements captured by the images, constrained by real physics. We do not impose any ad-hoc prior or energy minimization in the external surface, since the real and complete mechanics problem is solved. This means that we can also estimate the internal state of the objects, even in occluded areas, just by observing the external surface and the knowledge of material properties and geometry. Solving this problem in real time using a realistic constitutive law, usually non-linear, is out of reach for current systems. To overcome this difficulty, we solve off-line a parametrized problem that considers each source of variability in the problem as a new parameter and, consequently, as a new dimension in the formulation. Model Order Reduction methods allow us to reduce the dimensionality of the problem, and therefore, its computational cost, while preserving the visualization of the solution in the high-dimensionality space. This allows an accurate estimation of the object deformations, improving also the robustness in the 3D points estimation.

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