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Chair of Visual Computing
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Informatik

Chair of Visual Computing

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  • Research
    • Rendering and Visualization
    • Geometric Modeling and 3D Reconstruction
    • Virtual, Mixed, and Augmented Reality
    • Visual Computing for Digital Humanities and Social Sciences
    • Visual Healthcare Computing
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    • Vertiefungsrichtung Visual Computing
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  4. Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping

Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping

In page navigation: Publications
  • Publications 2020
  • Publications 2021
  • Publications 2022
    • Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping
    • Real-Time 3D Reconstruction of Human Vocal Folds via High-Speed Laser-Endoscopy

Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping

Philipp Kurth

Dr. Philipp Kurth, M. Sc.

Department of Computer Science
Chair of Computer Science 9 (Computer Graphics)

Room: Room 01.122-128
Cauerstraße 11
91058 Erlangen
  • Phone number: +49 9131 85-29928
  • Email: philipp.kurth@fau.de
  • Website: http://lgdv.cs.fau.de/people/card/philipp/kurth/

Office hours

Each week Tu, 14:00 - 15:00, nach Voranmeldung

Paper

  • Kurth P., Leuschner M., Stamminger M., Bauer F.:
    Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping
    In: IEEE Transactions on Visualization and Computer Graphics ISMAR 2022 (2022), p. 3607-3617
    ISSN: 1077-2626
    DOI: 10.1109/TVCG.2022.3203085
    URL: https://www.lgdv.tf.fau.de/?p=2413
    BibTeX: Download

Abstract

Projection mapping with inexpensive hardware often suffers from calibration errors that lead to visually compromised results. In this paper, we classify common errors that lead to typical visual artifacts. Based on this classification, we present the first content-aware brightness solver. It is tailored for high GPU performance, yet efficiently hides the most common calibration artifacts. Moreover, it is specifically designed to handle both single and larger networked projection mapping setups with minimal latency.

Video

Code

Code is available on github

 

Chair of Visual Computing
(Lehrstuhl für Graphische Datenverarbeitung)

Cauerstraße 11
91058 Erlangen
Deutschland
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