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CroP: Color Constancy Benchmark Dataset Generator (CROSBI ID 700308)

Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija

Banić, Nikola ; Koščević, Karlo ; Subašić, Marko ; Lončarić, Sven CroP: Color Constancy Benchmark Dataset Generator // Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing (ICVISP 2020). New York (NY): Association for Computing Machinery (ACM), 2020. doi: 10.1145/3448823.3448829

Podaci o odgovornosti

Banić, Nikola ; Koščević, Karlo ; Subašić, Marko ; Lončarić, Sven

engleski

CroP: Color Constancy Benchmark Dataset Generator

Implementing color constancy as a pre-processing step in contemporary digital cameras is of significant importance as it removes the influence of scene illumination on object colors. Several benchmark color constancy datasets have been created for the purpose of developing and testing new color constancy methods. However, they all have numerous drawbacks including a small number of images, erroneously extracted ground-truth illuminations, long histories of misuses, violations of their stated assumptions, etc. To overcome such and similar problems, in this paper a color constancy benchmark dataset generator is proposed. For a given camera sensor it enables generation of any number of realistic raw images taken in a subset of the real world, namely images of printed photographs. Datasets with such images share many positive features with other existing real-world datasets, while some of the negative features are completely eliminated. The generated images can be successfully used to train methods that afterward achieve high accuracy on real-world datasets. This opens the way for creating large enough datasets for advanced deep learning techniques. Experimental results are presented and discussed. The source code is available at http://www.fer.unizg.hr/ipg/resources/colorconsta ncy/.

color constancy ; data augmentation ; illumination estimation ; image dataset ; white balancing

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Podaci o prilogu

4

2020.

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objavljeno

978-1-4503-8953-2

10.1145/3448823.3448829

Podaci o matičnoj publikaciji

Proceedings of the 2020 4th International Conference on Vision, Image and Signal Processing (ICVISP 2020)

New York (NY): Association for Computing Machinery (ACM)

Podaci o skupu

2020 2nd International Symposium on Computer Graphics, Multimedia, and Image Processing (CGMIP 2020)

predavanje

09.12.2020-11.12.2020

Bangkok, Tajland

Povezanost rada

Računarstvo

Poveznice