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Sandro Huber

dblp:209/6060 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none

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

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

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 › parameterization
distortion optimization
0.312017
Autocuts: simultaneous distortion and cut optimization for UV mapping · ACM Trans. Graph. 2017
Geometric modeling and processing › surface parameterization
UV mapping
0.312017
Autocuts: simultaneous distortion and cut optimization for UV mapping · ACM Trans. Graph. 2017

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

geometric distortion energy minimization · 0.3
YearPublicationVenuePosition
2017 Autocuts: simultaneous distortion and cut optimization for UV mapping
abstract
We propose a UV mapping algorithm that jointly optimizes for cuts and distortion, sidestepping heuristics for placing the cuts. The energy we minimize is a state-of-the-art geometric distortion measure, generalized to take seams into account. Our algorithm is designed to support an interactive workflow: it optimizes UV maps on the fly, while the user can interactively move vertices, cut mesh parts, join seams, separate overlapping regions, and control the placement of the parameterization patches in the UV space. Our UV maps are of high quality in terms of both geometric distortion and cut placement, and compare favorably to those designed with traditional modeling tools. The UV maps can be created in a fraction of the time as existing methods, since our algorithm drastically alleviates the trial-and-error, iterative procedures that plague traditional UV mapping approaches.
Roi Poranne, Marco Tarini, Sandro Huber, Daniele Panozzo, Olga Sorkine-Hornung
ACM Trans. Graph.3