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

Kurth P, Leuschner M, Stamminger M, Bauer F (2022)

Publication Language: English

Publication Type: Journal article, Original article

Publication year: 2022

Journal

IEEE Transactions on Visualization and Computer Graphics Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: ISMAR 2022

Pages Range: 3607-3617

URI: https://www.lgdv.tf.fau.de/?p=2413

DOI: 10.1109/TVCG.2022.3203085

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.

Authors with CRIS profile

Philipp Kurth Professur für Mittlere und Neuere Kunstgeschichte Markus Leuschner Chair of Visual Computing (LGDV) Marc Stamminger Chair of Visual Computing (LGDV) Frank Bauer Chair of Visual Computing (LGDV)

Related research project(s)

Projection Mapping Oct. 1, 2014 - Oct. 1, 2025

How to cite

APA:

Kurth, P., Leuschner, M., Stamminger, M., & Bauer, F. (2022). Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping. IEEE Transactions on Visualization and Computer Graphics, ISMAR 2022, 3607-3617. https://doi.org/10.1109/TVCG.2022.3203085

MLA:

Kurth, Philipp, et al. "Content-Aware Brightness Solving and Error Mitigation in Large-Scale Multi-Projection Mapping." IEEE Transactions on Visualization and Computer Graphics ISMAR 2022 (2022): 3607-3617.

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