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Authors: Timo Viitanen ; Matias Koskela ; Kalle Immonen ; Markku Mäkitalo ; Pekka Jääskeläinen and Jarmo Takala

Affiliation: Tampere University of Technology, Finland

Keyword(s): Ray Tracing, Sparse Sampling, Image Reconstruction.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; High-Performance Computing and Parallel Rendering ; Lighting and Appearance ; Real-Time Rendering ; Rendering ; Rendering Algorithms ; Systems and Software Architectures for Rendering

Abstract: Ray tracing is an interesting rendering technique, but remains too slow for real-time applications. There are various algorithmic methods to speed up ray tracing through uneven screen-space sampling, e.g., foveated rendering where sampling is directed by eye tracking. Uneven sampling methods tend to require at least one sample per pixel, limiting their use in real-time rendering. We review recent work on image reconstruction from arbitrarily distributed samples, and argue that these will play major role in the future of real-time ray tracing, allowing a larger fraction of samples to be focused on regions of interest. Potential implementation approaches and challenges are discussed.

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Paper citation in several formats:
Viitanen, T.; Koskela, M.; Immonen, K.; Mäkitalo, M.; Jääskeläinen, P. and Takala, J. (2018). Sparse Sampling for Real-time Ray Tracing. In Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - GRAPP; ISBN 978-989-758-287-5; ISSN 2184-4321, SciTePress, pages 295-302. DOI: 10.5220/0006655802950302

@conference{grapp18,
author={Timo Viitanen. and Matias Koskela. and Kalle Immonen. and Markku Mäkitalo. and Pekka Jääskeläinen. and Jarmo Takala.},
title={Sparse Sampling for Real-time Ray Tracing},
booktitle={Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - GRAPP},
year={2018},
pages={295-302},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006655802950302},
isbn={978-989-758-287-5},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 13th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2018) - GRAPP
TI - Sparse Sampling for Real-time Ray Tracing
SN - 978-989-758-287-5
IS - 2184-4321
AU - Viitanen, T.
AU - Koskela, M.
AU - Immonen, K.
AU - Mäkitalo, M.
AU - Jääskeläinen, P.
AU - Takala, J.
PY - 2018
SP - 295
EP - 302
DO - 10.5220/0006655802950302
PB - SciTePress