Reflectance and Illumination Estimation for Realistic Augmentations of Real Scenes
The acquisition of surface material properties and lighting conditions is a fundamental step for photo-realistic Augmented Reality (AR). In this paper, we present a new method for the estimation of diffuse and specular reflectance properties of indoor real static scenes. Using an RGB-D sensor, we further estimate the 3D position of light sources responsible for specular phenomena and propose a novel photometry-based classification for all the 3D points. Our algorithm allows convincing AR results such as realistic virtual shadows as well as proper illumination and specularity occlusions.
