Examinando por Autor "Perez, Jesus"

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Modeling and Estimation of Nonlinear Skin Mechanics for Animated Avatars
(2020-04-17) Romero, Cristian; Otaduy, Miguel A.; Casas, Dan; Perez, Jesus
Data-driven models of human avatars have shown very accurate representations of static poses with soft-tissue deformations. However they are not yet capable of precisely representing very nonlinear deformations and highly dynamic effects. Nonlinear skin mechanics are essential for a realistic depiction of animated avatars interacting with the environment, but controlling physics-only solutions often results in a very complex parameterization task. In this work, we propose a hybrid model in which the soft-tissue deformation of animated avatars is built as a combination of a data-driven statistical model, which kinematically drives the animation, an FEM mechanical simulation. Our key contribution is the definition of deformation mechanics in a reference pose space by inverse skinning of the statistical model. This way, we retain as much as possible of the accurate static data-driven deformation and use a custom anisotropic nonlinear material to accurately represent skin dynamics. Model parameters including the heterogeneous distribution of skin thickness and material properties are automatically optimized from 4D captures of humans showing soft-tissue deformations.
Non-invasive procedure for acquisition of mechanical properties of the torso
(-, 2022) Koutras, Christos; Shayestehpour, Hamed; Perez, Jesus; Wong, Christian; Arnesen, Anna; Rasmussen, John; Otaduy, Miguel A.
Computational methods promise benefits for the design of braces to manage adolescent idiopathic scoliosis. However, computational methods for the design of scoliosis braces suffer an important challenge: they require a personalized model of the patient’s torso biomechanics. The biggest difficulty in building a personalized model of the torso is defining its mechanical parametrization. In this work, we present a non-invasive procedure to obtain simultaneously force and deformation that characterize the mechanical response of the torso. We have tested the method on ten scoliotic patients, and we demonstrate its sensitivity by quantifying the range of forces and Cobb angles during the procedure.