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Revisiting gray pixel for statistical illumination estimation

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Revisiting gray pixel for statistical illumination estimation. / Qian, Yanlin; Pertuz, Said; Nikkanen, Jarno; Kämäräinen, Joni-Kristian; Matas, Jiri.

VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. ed. / Andreas Kerren; Christophe Hurter; Jose Braz. SCITEPRESS, 2019. p. 36-46.

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Harvard

Qian, Y, Pertuz, S, Nikkanen, J, Kämäräinen, J-K & Matas, J 2019, Revisiting gray pixel for statistical illumination estimation. in A Kerren, C Hurter & J Braz (eds), VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS, pp. 36-46, International Conference on Computer Vision Theory and Applications, Prague, Czech Republic, 25/02/19. https://doi.org/10.5220/0007406900360046

APA

Qian, Y., Pertuz, S., Nikkanen, J., Kämäräinen, J-K., & Matas, J. (2019). Revisiting gray pixel for statistical illumination estimation. In A. Kerren, C. Hurter, & J. Braz (Eds.), VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (pp. 36-46). SCITEPRESS. https://doi.org/10.5220/0007406900360046

Vancouver

Qian Y, Pertuz S, Nikkanen J, Kämäräinen J-K, Matas J. Revisiting gray pixel for statistical illumination estimation. In Kerren A, Hurter C, Braz J, editors, VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. SCITEPRESS. 2019. p. 36-46 https://doi.org/10.5220/0007406900360046

Author

Qian, Yanlin ; Pertuz, Said ; Nikkanen, Jarno ; Kämäräinen, Joni-Kristian ; Matas, Jiri. / Revisiting gray pixel for statistical illumination estimation. VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. editor / Andreas Kerren ; Christophe Hurter ; Jose Braz. SCITEPRESS, 2019. pp. 36-46

Bibtex - Download

@inproceedings{425048405bed4e2a9c0132ae0a79a752,
title = "Revisiting gray pixel for statistical illumination estimation",
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.",
keywords = "Color Constancy, Gray Pixel, Illumination Estimation",
author = "Yanlin Qian and Said Pertuz and Jarno Nikkanen and Joni-Kristian K{\"a}m{\"a}r{\"a}inen and Jiri Matas",
year = "2019",
doi = "10.5220/0007406900360046",
language = "English",
pages = "36--46",
editor = "Andreas Kerren and Christophe Hurter and Jose Braz",
booktitle = "VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications",
publisher = "SCITEPRESS",

}

RIS (suitable for import to EndNote) - Download

TY - GEN

T1 - Revisiting gray pixel for statistical illumination estimation

AU - Qian, Yanlin

AU - Pertuz, Said

AU - Nikkanen, Jarno

AU - Kämäräinen, Joni-Kristian

AU - Matas, Jiri

PY - 2019

Y1 - 2019

N2 - 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.

AB - 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.

KW - Color Constancy

KW - Gray Pixel

KW - Illumination Estimation

U2 - 10.5220/0007406900360046

DO - 10.5220/0007406900360046

M3 - Conference contribution

SP - 36

EP - 46

BT - VISIGRAPP 2019 - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications

A2 - Kerren, Andreas

A2 - Hurter, Christophe

A2 - Braz, Jose

PB - SCITEPRESS

ER -