Online illumination estimation of outdoor scenes based on videos containing no shadow area

• Published in: Science China. Information sciences Vol. 56; no. 3; pp. 1 - 11
• Main Authors: Xing, GuanYu, Zhou, XueHong, Liu, YanLi, Qin, XueYing, Peng, QunSheng
• Format: Journal Article
• Language: English
• Published: Heidelberg SP Science China Press 01.03.2013; Springer Nature B.V
• Subjects: Augmented reality; Coefficient of variation; Computer Science; Constraints; Dynamics; Illumination; Information Systems and Communication Service; Least squares method; Lighting; Occlusion; On-line systems; Online; Outdoor; Research Paper; Shadows; Skylights; 估计; 光照; 在线; 基础; 室外场景; 户外照明; 视频序列; 阴影区; outdoor scenes; non-uniform skylight distribution; online illumination estimation; limited scene reconstruction; videos containing no shadow areas
• ISSN: 1674-733X; 1869-1919
• DOI: 10.1007/s11432-012-4780-7

Real-time estimation of outdoor illumination is one of the key issues for ensuring the illumination consistency of augmented reality. In this paper, we propose a novel framework to estimate the dynamic illumi- nation of outdoor scenes based on an online video sequence captured by a fixed camera. All existing approaches are based on two assumptions, i.e. there exist some shadow areas in the scene and the distribution of the skylight is uniform over the sky. Both assumptions greatly simplify the problem of illumination estimation of outdoor scenes, but they also limit the applicability as well as the accuracy of these approaches. This paper presents a new approach that breaks these two hard constraints. It recovers the lighting parameters of outdoor scenes containing no shadow area through solving a constrained linear least squares problem. By representing the skylight as a parameterized model incorporating an occlusion coefficient, the proposed approach can handle the dynamic variation of non-uniform skylight distribution. Experimental results demonstrate the potential of our approach.