Design and Creation of a Multi-illuminant Scene Image Dataset

Most of the computational color constancy approaches are based on the assumption of a uniform illumination in the scene which is not the case in many real world scenarios. A crucial ingredient in developing color constancy algorithms which can handle these scenarios is a dataset of such images with accurate illumination ground truth to be used both for estimating the parameters and for evaluating the performance. Such datasets are rare due to the complexity of the procedure involved in capturing them. To this end, we provide a framework for capturing such dataset and propose our multi-illuminant scene image dataset with pixel-wise accurate ground truth. Our dataset consists of 6 different scenes under 5 illumination conditions provided by two or three distinctly colored illuminants. The scenes are made up of complex colored objects presenting diffuse and specular reflections. We present quantitative evaluation of the accuracy of our proposed ground truth and show that the effect of ambient light is negligible.