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Reconstructing Dynamic 3D Models with Small Data by Integrating Position-Based Dynamics and PDE-Based Modelling

Abstract: Simulation with position-based dynamics is very popular due to its high efficiency. However, it has the weaknesses of lacking details when too few vertices are involved in simulation and inefficiency when too many vertices are used for simulation. To tackle this problem, in this paper, we propose a new method of reconstructing dynamic 3D models with small data. The core elements of the proposed approach are a curve-represented geometric model and a physics-based mathematical model defined by dynamic partial differential equations. We first use the simulation method of position-based dynamics to generate a group of keyframe poses, which are used to create the deformation animation of a 3D model. Then, wireframe curves are extracted from skin deformation shapes of the 3D model at different keyframe poses. A physics-based mathematical model defined by dynamic partial differential equations is proposed. Its closed-form solution is obtained to represent the extracted curves, which are used to reconstruct the deformation models at different keyframe poses. Experimental examples and comparisons made in this paper indicate that the proposed method of reconstructing dynamic 3D models can greatly reduce data size while keeping good details.

 Fuente: Mathematics, 2022, 10(5), 821

Editorial: MDPI

 Fecha de publicación: 04/03/2022

Nº de páginas: 24

Tipo de publicación: Artículo de Revista

 DOI: 10.3390/math10050821

ISSN: 2227-7390

Proyecto español: TIN2017-89275-R

Proyecto europeo: info:eu-repo/grantAgreement/EC/H2020/778035/EU/PDE-based geometric modelling, image processing, and shape reconstruction/PDE-GIR/

Autores/as

FANG, JUNHENG

CHAUDHRY, EHTZAZ

YOU, LIHUA

ZHANG, JIANJUN