Publication
Dirichlet energy for analysis and synthesis of soft maps
Abstract
Soft maps taking points on one surface to probability distributions on another are attractive for representing surface mappings in the presence of symmetry, ambiguity, and combinatorial complexity. Few techniques, however, are available to measure their continuity and other properties. To this end, we introduce a novel Dirichlet energy for soft maps generalizing the classical map Dirichlet energy, which measures distortion by computing how soft maps transport probabilistic mass from one distribution to another. We formulate the computation of the Dirichlet energy in terms of a differential equation and provide a finite elements discretization that enables all of the quantities introduced to be computed efficiently. We demonstrate the effectiveness of our framework for understanding soft maps arising from various sources. Furthermore, we suggest how these energies can be applied to generate continuous soft or point-to-point maps.
Download publicationRelated Resources
See what’s new.
2023
Embedding Experiential Design Knowledge in Interactive Knowledge GraphsHow experiential knowledge from professional designers can be…
2024
Three Ways to Keep Learning from AU All Year LongCheck out how to continue learning from AU 2023 all year long…
2013
Solutions for Scalability in Building Information Modeling and Simulation-Based DesignSimulation-based design can enable a number of advanced architectural…
Get in touch
Something pique your interest? Get in touch if you’d like to learn more about Autodesk Research, our projects, people, and potential collaboration opportunities.
Contact us