Shadows & Lumination: Two-illuminant multiple cameras color constancy dataset. (15th August 2023)

• Record Type: Journal Article
• Authors: Domislović, Ilija; Vršnak, Donik; Subašić, Marko; Lončarić, Sven
• Is Part Of: Expert systems with applications. Volume 224(2023)
• Publication Date: 2023-08-15
• Subjects: Multi-illuminant dataset -- Color constancy -- Image color analysis -- Image processing -- Image segmentation; Expert systems (Computer science) -- Periodicals; Systèmes experts (Informatique) -- Périodiques; Electronic journals; 006.33
• DOI: 10.1016/j.eswa.2023.120045
• Languages: English
• ISSNs: 0957-4174

Abstract

Abstract: In this paper, we introduce a new large-scale publicly available color constancy dataset which we are calling the Shadows & Lumination dataset. The dataset contains 2500 minimally processed images from various indoor, outdoor, and night-time scenes. This dataset is GDPR-compliant, as we masked out all sensitive private information from the images. Unlike most other color constancy datasets, our dataset contains real-world images with two illuminants is appropriate for multi-illuminant estimation. In addition to the illumination, we provide a binary segmentation mask for each image. In the segmentation mask, we divide the image into two regions, where each region is illuminated by only one of the illuminants. We give an explanation of the methodology used to create the dataset. For dataset creation, we used five cameras: Canon 5D, Canon 550D, Sony α 300, Panasonic FZ1000, and the Motorola one fusion+ mobile camera. Finally, we tested several state-of-the-art illumination estimation and image segmentation models on our dataset. The dataset is publicly available 1 . This paper also benchmarks several illumination estimation methods as well as several image segmentation methods on our dataset. Highlights: Large-scale public dataset for two-illuminant color constancy. Detailed manually annotated per pixel illumination segmentation mask included. Image acquisition and labeling methodology provided. Existing state-of-the-art methods were tested on the new dataset.