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, i.e., 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) regulations. Furthermore, the effect of color shading for mobile images can be evaluated with INTEL-TAU, as we provide both corrected and uncorrected versions of the raw data. We provide in this paper evaluation of several color constancy approaches
翻译:在本文中,我们描述了用于照明估计的新的大型数据集。这个数据集称为INTEL-TAU,总共包含7022个图像,这使它成为可用于照明估计研究的最大高分辨率数据集。使用三种不同的照相模型,即Canon 5DSR、Nikon D810和Sony IMX135拍摄的场景种类繁多,使得数据集适合于评价不同照明估计技术的相机和场景。隐私掩蔽是针对敏感信息,例如面部进行的。因此,数据集与新的一般数据保护条例(GDPR)相一致。此外,移动图像的彩色遮光效果可以与INTEL-TAU一起评估,因为我们既提供了原始数据的校正版本,也提供了未经校正版本。我们在本文中对几种颜色耐久方法进行了评估。我们在本文中提供了对几种颜色耐久性方法的评估。