Towards a complete dense geometric and photometric reconstruction under varying pose and illumination

This paper proposes a novel framework to construct a geometric and pho-tometric model of a viewed object that can be used for visualisation in ar-bitrary pose and illumination. The method is solely based on images and does not require any specialised equipment. We assume that the object has a piece-wise smooth surface and that its reflectance can be modelled using a parametric bidirectional reflectance distribution function. Without assum-ing any prior knowledge on the object, geometry and reflectance have to be estimated simultaneously and occlusion and shadows have to be treated con-sistently. We exploit the geometric and photometric consistency using the fact that surface orientation and reflectance are local invariants. In a first im-plementation, we demonstrate the method using a Lambertian object placed on a turn-table and illuminated by a number of unknown point light-sources. A discrete voxel model is initialised to the visual hull and voxels identified as inconsistent with the invariants are removed iteratively. The resulting model is used to render images in novel pose and illumination.