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Stefan Trumpler

dblp:184/7386 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2016
—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
Rendering · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Rendering › appearance acquisition
light transport acquisition
0.212016
VITRAIL: Acquisition, Modeling, and Rendering of Stained Glass · IEEE Trans. Image Process. 2016
Rendering
relighting
0.212016
VITRAIL: Acquisition, Modeling, and Rendering of Stained Glass · IEEE Trans. Image Process. 2016
Rendering
material appearance
0.112016
VITRAIL: Acquisition, Modeling, and Rendering of Stained Glass · IEEE Trans. Image Process. 2016

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

sparse regularization · 0.2light transport matrix · 0.2image-based prior · 0.2compressive sensing · 0.2
YearPublicationVenuePosition
2016 VITRAIL: Acquisition, Modeling, and Rendering of Stained Glass
abstract
Stained glass windows are designed to reveal their powerful artistry under diverse and time-varying lighting conditions; virtual relighting of stained glass, therefore, represents an exceptional tool for the appreciation of this age old art form. However, as opposed to most other artifacts, stained glass windows are extremely difficult if not impossible to analyze using controlled illumination because of their size and position. In this paper, we present novel methods built upon image based priors to perform virtual relighting of stained glass artwork by acquiring the actual light transport properties of a given artifact. In a preprocessing step, we build a material-dependent dictionary for light transport by studying the scattering properties of glass samples in a laboratory setup. We can now use the dictionary to recover a light transport matrix in two ways: under controlled illuminations the dictionary constitutes a sparsifying basis for a compressive sensing acquisition, while in the case of uncontrolled illuminations the dictionary is used to perform sparse regularization. The proposed basis preserves volume impurities and we show that the retrieved light transport matrix is heterogeneous, as in the case of real world objects. We present the rendering results of several stained glass artifacts, including the Rose Window of the Cathedral of Lausanne, digitized using the presented methods.
Niranjan Thanikachalam, Loïc Baboulaz, Paolo Prandoni, Stefan Trumpler, Sophie Wolf, Martin Vetterli
IEEE Trans. Image Process.4