Differential Representations for Mesh Processing

By Olga Sorkine-Hornung. 2006

303 citations recorded by the source corpus.

Subfields: Computational Mechanics, Computer Graphics and Computer-Aided Design

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In Computational Mechanics

In Computer Graphics and Computer-Aided Design

Citations in the corpus

Graph Laplacians and their Convergence on Random Neighborhood Graphs (2006, methodology): “Sorkine (2006) . If one has gathered points of a curved object with a laser scanner it is likely that the points have a non-uniform distribution on the object.”
On Linear Variational Surface Deformation Methods (2008, unknown): “A concise summary of Laplacian-based mesh processing techniques appeared in [56].”
A generalized grid connectivity–based parameterization for subsurface flow model calibration (2011, methodology): “Of its many definitions, we specifically construct the grid Laplacian as L = D − A [Mohar, 1997; Sorkine, 2006; von Luxburg, 2006; Spielman and Teng, 2007], or, analogously, as”
ClothCap (2017, background): “The Laplacian term : In order to keep the garment meshes well behaved we include a Laplacian term (Sorkine 2006; Sorkine et al. 2004).”
As-rigid-as-possible surface modeling (2007, background): “It also turns out that it can be interpreted as an iterative improvement of the now-common discrete Laplacian modeling frameworks [Sor06], which greatly facilitates its adoption into existing modeling frameworks.”
A Survey on Shape Correspondence (2011, methodology): “For this step, one of the recently proposed deformation methods can be utilized (as in the surveys [Sor06, SSP07]).”
3D-CODED: 3D Correspondences by Deep Deformation (2018, methodology): “The Laplacian matrix L is deﬁned as : This is an approximation of the following integral as explained in [42]. where: –”
MakeItTalk: Speaker-Aware Talking Head Animation (2020, background): “…(a) the distance between the registered reference landmark positions ˆp 𝑡 and predicted ones p 𝑡 , and (b) the distance between their respective graph Laplacian coordinates, which promotes correct placement of landmarks with respect to each other and preserves facial shape details [Sorkine 2006].”
Laplace-Beltrami eigenfunctions for deformation invariant shape representation (2007, unknown): “Applications of Laplace-Beltrami: Discrete versions of Laplace and Laplace-Beltrami operators, usually both referred to as Laplacians, found many applications in geometry processing [Sor06].”