Results 71 to 80 of about 1,147 (194)

SDFs from Unoriented Point Clouds using Neural Variational Heat Distances

Computer Graphics Forum, EarlyView.
We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from unoriented point clouds. We first compute a small time step of heat flow (middle) and then use its gradient directions to solve for a neural SDF (right). Abstract We propose a novel variational approach for computing neural Signed Distance Fields (SDF) from ...
Samuel Weidemaier, Florine Hartwig, Josua Sassen, Sergio Conti, Mirela Ben‐Chen, Martin Rumpf   +5 more
wiley   +1 more source

A Semi‐Analytical Energy Model for Particle‐Based Fluid Simulation Involving Complex Moving Boundaries

Computer Graphics Forum, EarlyView.
Abstract While semi‐analytical boundary handling techniques have proven effective for modeling particle‐based fluid‐solid interactions, they can become unstable when applied to mesh boundaries undergoing dynamic motion or featuring complex, sharp geometries.
Junyuan Liu, Shusen Liu, Yuzhong Guo, Ruikai Liang, Ying Li, Xiaowei He   +5 more
wiley   +1 more source

A Study on Dimensionality Reduction and Parameters for Hyperspectral Imagery Based on Manifold Learning

Sensors
With the rapid advancement of remote-sensing technology, the spectral information obtained from hyperspectral remote-sensing imagery has become increasingly rich, facilitating detailed spectral analysis of Earth’s surface objects.
Wenhui Song, Xin Zhang, Guozhu Yang, Yijin Chen, Lianchao Wang, Hanghang Xu   +5 more
doaj   +1 more source

Locally conformally Hessian and statistical manifolds

Journal of Geometry and Physics, 2023
A statistical manifold $\left(M,D,g\right)$ is a manifold $M$ endowed with a torsion-free connection $D$ and a Riemannian metric $g$ such that the tensor $D g$ is totally symmetric. If $D$ is flat then $\left(M,g,D\right)$ is a Hessian manifold. A locally conformally Hessian (l.c.H) manifold is a quotient of a Hessian manifold $(C,\nabla,g)$ such that ...
openaire   +3 more sources

Fast Injective Mesh Parameterization via Beltrami Coefficient Prolongation

Computer Graphics Forum, EarlyView.
Abstract We present a highly efficient and robust method for free boundary injective parameterization of disk‐like triangle meshes with low isometric distortion. Harmonic function–based approaches, grounded in a strong mathematical framework, are widely employed.
G. Fargion, O. Weber
wiley   +1 more source

Projective Vector Fields on Semi-Riemannian Manifolds

Mathematics
This paper explores the properties of projective vector fields on semi-Riemannian manifolds. The main result establishes that if a projective vector field P on such a manifold is also a conformal vector field with potential function ψ and the vector ...
Norah Alshehri, Mohammed Guediri
doaj   +1 more source

Interpolated Adaptive Linear Reduced Order Modeling for Deformation Dynamics

Computer Graphics Forum, EarlyView.
Abstract Linear reduced‐order modeling (ROM) is widely used for efficient simulation of deformation dynamics, but its accuracy is often limited by the fixed linearization of the reduced mapping. We propose a new adaptive strategy for linear ROM that allows the reduced mapping to vary dynamically in response to the evolving deformation state ...
Y. Tao, M. Chiaramonte, P. Fernandez
wiley   +1 more source

Affinification: A Fine Approximation of Deformations

Computer Graphics Forum, EarlyView.
Abstract We introduce affinification, a novel method for accelerating physics‐based animation of elastic solids. During a time‐dependent simulation, our method automatically partitions the space into affine and elastic regions depending on the deformation.
A. Mercier‐Aubin, T. Schneider, P.G. Kry, S. Andrews   +3 more
wiley   +1 more source

The Pontryagin Forms of Hessian Manifolds [PDF]

, 2016
We show that Hessian manifolds of dimensions 4 and above must have vanishing Pontryagin forms. This gives a topological obstruction to the existence of Hessian metrics. We find an additional explicit curvature identity for Hessian 4-manifolds. By contrast, we show that all analytic Riemannian 2-manifolds are Hessian.
Armstrong, J.; id_orcid 0000-0002-4232-9555, Amari, S.   +1 more
openaire  

Progressively Projected Newton's Method

Computer Graphics Forum, EarlyView.
Abstract Newton's Method is widely used to find the solution of complex non‐linear simulation problems. To guarantee a descent direction, it is common practice to clamp the negative eigenvalues of each element Hessian prior to assembly—a strategy known as Projected Newton (PN)—but this perturbation often hinders convergence.
J. A. Fernández‐Fernández, F. Löschner, J. Bender   +2 more
wiley   +1 more source