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Link to original content: https://doi.org/10.5220/0012418900003660
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Authors: Takaoki Ueda ; Ryo Kawahara and Takahiro Okabe

Affiliation: Department of Artificial Intelligence, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan

Keyword(s): Direct-Global Separation, Projector-Camera System, Projection Patterns, End-to-End Optimization.

Abstract: Separating the direct component such as diffuse reflection and specular reflection and the global component such as inter-reflection and subsurface scattering is important for various computer vision and computer graphics applications. Conventionally, high-frequency patterns designed by physics-based model or signal processing theory are projected from a projector to a scene, but their assumptions do not necessarily hold for real images due to the shallow depth of field of a projector and the limited spatial resolution of a camera. Accordingly, in this paper, we propose a data-driven approach for direct-global separation. Specifically, our proposed method learns not only the separation module but also the imaging module, i.e. the projection patterns at the same time in an end-to-end manner. We conduct a number of experiments using real images captured with a projector-camera system, and confirm the effectiveness of our method.

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Paper citation in several formats:
Ueda, T.; Kawahara, R. and Okabe, T. (2024). Learning Projection Patterns for Direct-Global Separation. In Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-679-8; ISSN 2184-4321, SciTePress, pages 599-606. DOI: 10.5220/0012418900003660

@conference{visapp24,
author={Takaoki Ueda. and Ryo Kawahara. and Takahiro Okabe.},
title={Learning Projection Patterns for Direct-Global Separation},
booktitle={Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2024},
pages={599-606},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012418900003660},
isbn={978-989-758-679-8},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 19th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Learning Projection Patterns for Direct-Global Separation
SN - 978-989-758-679-8
IS - 2184-4321
AU - Ueda, T.
AU - Kawahara, R.
AU - Okabe, T.
PY - 2024
SP - 599
EP - 606
DO - 10.5220/0012418900003660
PB - SciTePress