Estimation of Multiple Illuminants from a Single Image of Arbitrary Known Geometry

We present a new method for the detection and estimation of multiple illuminants, using one image of any object with known geometry and Lambertian reflectance. Our method obviates the need to modify the imaged scene by inserting calibration objects of any particular geometry, relying instead on partial knowledge of the geometry of the scene. Thus, the recovered multiple illuminants can be used both for image-based rendering and for shape reconstruction. We first develop our method for the case of a sphere with known size, illuminated by a set of directional light sources. In general, each point of such a sphere will be illuminated by a subset of these sources. We propose a novel, robust way to segment the surface into regions, with each region illuminated by a different set of sources. The regions are separated by boundaries consisting of critical points (points where one illuminant is perpendicular to the normal). Our region-based recursive least squares method is impervious to noise ...

• Type: Conference
• Year: 2002
• Where: ECCV
• Authors: Yang Wang, Dimitris Samaras
• Keywords: Arbitrary Smooth Geometry, Computer Vision, Directional Light Sources, ECCV 2002, Multiple Illuminants, Particular Geometry, Squares Method