INTEL-TAU: A Color Constancy Dataset

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http://hdl.handle.net/10138/334920

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F. Laakom, J. Raitoharju, J. Nikkanen, A. Iosifidis and M. Gabbouj, "INTEL-TAU: A Color Constancy Dataset," in IEEE Access, vol. 9, pp. 39560-39567, 2021, https://doi.org/10.1109/access.2021.3064382

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Title: INTEL-TAU: A Color Constancy Dataset
Author: Laakom, Firas; Raitoharju, Jenni; Nikkanen, Jarno; Iosifidis, Alexandros; Gabbouj, Moncef
Publisher: IEEE
Date: 2021
Language: en
Belongs to series: IEEE Access 9, 39560-39567
ISSN: 2169-3536
DOI: https://doi.org/10.1109/access.2021.3064382
URI: http://hdl.handle.net/10138/334920
Abstract: In this paper, we describe a new large dataset for illumination estimation. This dataset, called INTEL-TAU, contains 7022 images in total, which makes it the largest available high-resolution dataset for illumination estimation research. The variety of scenes captured using three different camera models, namely Canon 5DSR, Nikon D810, and Sony IMX135, makes the dataset appropriate for evaluating the camera and scene invariance of the different illumination estimation techniques. Privacy masking is done for sensitive information, e.g., faces. Thus, the dataset is coherent with the new General Data Protection Regulation (GDPR). Furthermore, the effect of color shading for mobile images can be evaluated with INTEL-TAU dataset, as both corrected and uncorrected versions of the raw data are provided. Furthermore, this paper benchmarks several color constancy approaches on the proposed dataset.
Subject: image color analysis
lightning
cameras
estimation
databases
training
privacy
Subject (ysa): benchmarking
menetelmät
vertailu
analyysi
värit
kamerat
tiedostot
arviointi
valokuvat
valaistus
Rights: CC BY 4.0


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