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Authors: Yanlin Qian 1 ; Said Pertuz 2 ; Jarno Nikkanen 3 ; Joni-Kristian Kämäräinen 2 and Jiri Matas 4

Affiliations: 1 Laboratory of Signal Processing, Tampere University of Technology, Finland, Center for Machine Perception, Czech Technical University in Prague and Czech Republic ; 2 Laboratory of Signal Processing, Tampere University of Technology and Finland ; 3 Intel Finland and Finland ; 4 Center for Machine Perception, Czech Technical University in Prague and Czech Republic

Keyword(s): Illumination Estimation, Color Constancy, Gray Pixel.

Related Ontology Subjects/Areas/Topics: Applications and Services ; Color and Texture Analyses ; Computational Photography ; Computer Vision, Visualization and Computer Graphics ; Digital Photography ; Image and Video Analysis ; Image Formation and Preprocessing ; Image Formation, Acquisition Devices and Sensors ; Rendering

Abstract: We present a statistical color constancy method that relies on novel gray pixel detection and mean shift clustering. The method, called Mean Shifted Grey Pixel – MSGP, is based on the observation: true-gray pixels are aligned towards one single direction. Our solution is compact, easy to compute and requires no training. Experiments on two real-world benchmarks show that the proposed approach outperforms state-of-the-art methods in the camera-agnostic scenario. In the setting where the camera is known, MSGP outperforms all statistical methods.

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Paper citation in several formats:
Qian, Y.; Pertuz, S.; Nikkanen, J.; Kämäräinen, J. and Matas, J. (2019). Revisiting Gray Pixel for Statistical Illumination Estimation. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 36-46. DOI: 10.5220/0007406900360046

@conference{visapp19,
author={Yanlin Qian. and Said Pertuz. and Jarno Nikkanen. and Joni{-}Kristian Kämäräinen. and Jiri Matas.},
title={Revisiting Gray Pixel for Statistical Illumination Estimation},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP},
year={2019},
pages={36-46},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007406900360046},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 4: VISAPP
TI - Revisiting Gray Pixel for Statistical Illumination Estimation
SN - 978-989-758-354-4
IS - 2184-4321
AU - Qian, Y.
AU - Pertuz, S.
AU - Nikkanen, J.
AU - Kämäräinen, J.
AU - Matas, J.
PY - 2019
SP - 36
EP - 46
DO - 10.5220/0007406900360046
PB - SciTePress

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