Rogelio Ortigosa

dblp:200/2626 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-4542-2237ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
distortion energy minimization
0.712023
Geometric Optimisation Via Spectral Shifting · ACM Trans. Graph. 2023
Geometric modeling and processing
geometry optimization
0.712023
Geometric Optimisation Via Spectral Shifting · ACM Trans. Graph. 2023

Methods — techniques the papers use, named apart from their topics

projected newton solver · 0.7hessian stabilization · 0.7
YearPublicationVenuePosition
2023 Geometric Optimisation Via Spectral Shifting
abstract
We present a geometric optimisation framework that can recover fold-over free maps from non-injective initial states using popular flip-preventing distortion energies. Since flip-preventing energies are infinite for folded configurations, we propose a new regularisation scheme that shifts the singular values of the deformation gradient. This allow us to re-use many existing algorithms, especially locally injective methods for initially folded maps. Our regularisation is suitable for both singular value- and invariant-based formulations, and systematically contributes multiple stabilisers to the Hessian. In contrast to proxy-based techniques, we maintain second-order convergence. Compact expressions for the energy eigensystems can be obtained for our extended stretch invariants, enabling the use of fast projected Newton solvers. Although spectral shifting in general has no theoretical guarantees that the global minimum is an injection, extensive experiments show that our framework is fast and extremely robust in practice, and capable of generating high-quality maps from severely distorted, degenerate and folded initialisations.
Roman Poya, Rogelio Ortigosa, Theodore Kim
ACM Trans. Graph.2