Dirichlet energy of Delaunay meshes and intrinsic Delaunay triangulations

Abstract The Dirichlet energy of a smooth function measures how variable the function is. Due to its deep connection to the Laplace–Beltrami operator, Dirichlet energy plays an important role in digital geometry processing. Given a 2-manifold triangle mesh M with vertex set V , the generalized Rippa’s theorem shows that the Dirichlet energy among all possible triangulations of V arrives at its minimum on the intrinsic Delaunay triangulation (IDT) of V . Recently, Delaunay meshes (DM) – a special type of triangle mesh whose IDT is the mesh itself – were proposed, which can be constructed by splitting mesh edges and refining the triangulation to ensure the Delaunay condition. This paper focuses on Dirichlet energy for functions defined on DMs. Given an arbitrary function f defined on the original mesh vertices V , we present a scheme to assign function values to the DM vertices V n e w ⊃ V by interpolating f . We prove that the Dirichlet energy on DM is no more than that on the IDT. Furthermore, among all possible functions defined on V n e w by interpolating f , our scheme attains the global minimum of Dirichlet energy on a given DM.

[1]  Tamal K. Dey,et al.  Delaunay Mesh Generation , 2012, Chapman and Hall / CRC computer and information science series.

[2]  G. Dziuk Finite Elements for the Beltrami operator on arbitrary surfaces , 1988 .

[3]  Alexander I. Bobenko,et al.  A Discrete Laplace–Beltrami Operator for Simplicial Surfaces , 2005, Discret. Comput. Geom..

[4]  Guoliang Xu,et al.  A general framework for surface modeling using geometric partial differential equations , 2008, Comput. Aided Geom. Des..

[5]  Mathieu Desbrun,et al.  Weighted Triangulations for Geometry Processing , 2014, ACM Trans. Graph..

[6]  Yong-Jin Liu,et al.  Delaunay mesh simplification with differential evolution , 2018, ACM Trans. Graph..

[7]  Atsuyuki Okabe,et al.  Spatial Tessellations: Concepts and Applications of Voronoi Diagrams , 1992, Wiley Series in Probability and Mathematical Statistics.

[8]  Guoliang Xu Convergence of discrete Laplace-Beltrami operators over surfaces , 2004 .

[9]  Mark Meyer,et al.  Intrinsic Parameterizations of Surface Meshes , 2002, Comput. Graph. Forum.

[10]  Giuseppe Patanè,et al.  STAR ‐ Laplacian Spectral Kernels and Distances for Geometry Processing and Shape Analysis , 2016, Comput. Graph. Forum.

[11]  Yong-Jin Liu,et al.  Efficient construction and simplification of Delaunay meshes , 2015, ACM Trans. Graph..

[12]  Ligang Liu,et al.  Fast Wavefront Propagation (FWP) for Computing Exact Geodesic Distances on Meshes , 2015, IEEE Transactions on Visualization and Computer Graphics.

[13]  Igor Rivin Euclidean Structures on Simplicial Surfaces and Hyperbolic Volume , 1994 .

[14]  Keenan Crane,et al.  Navigating intrinsic triangulations , 2019, ACM Trans. Graph..

[15]  Keenan Crane,et al.  Geodesics in heat: A new approach to computing distance based on heat flow , 2012, TOGS.

[16]  F. Morgan Real analysis and applications : including Fourier series and the calculus of variations , 2005 .

[17]  Samuel Rippa,et al.  Minimal roughness property of the Delaunay triangulation , 1990, Comput. Aided Geom. Des..

[18]  Kai Tang,et al.  Approximate Delaunay mesh reconstruction and quality estimation from point samples , 2015, J. Comput. Appl. Math..

[19]  Ying He,et al.  Constructing Intrinsic Delaunay Triangulations from the Dual of Geodesic Voronoi Diagrams , 2015, ACM Trans. Graph..

[20]  Braxton Osting,et al.  Minimal Dirichlet Energy Partitions for Graphs , 2013, SIAM J. Sci. Comput..

[21]  Ulrich Pinkall,et al.  Computing Discrete Minimal Surfaces and Their Conjugates , 1993, Exp. Math..

[22]  M. Alexa,et al.  Discrete Laplacians on general polygonal meshes , 2011, ACM Transactions on Graphics.