Using Polarization to Determine Intrinsic Surface Properties

Among properties computer vision attempts to extract from images are: local shape, intrinsic reflection parameters, and roughness because they are all crucial to the success of image interpretation in general and to realistic surface modeling in particular. We seek light reflection phenomena and reflectance models that could better capture the relation of reflected light parameters to the local properties of the observed surface. In addition to the relation intensity–shape studied in computer vision for a long time, we study the relation of other light characteristics to local shape. We started by focusing on light polarization state. We found that the generalization of the Lambert's reflectance model based on Fresnel coefficients, as proposed by Wolff, correctly predicts the polarization state of light reflected on smooth dielectrics. Both the light incidence and the viewer plane orientations may be measured to estimate the surface normal if light position relative to the observer is known. It is demonstrated that inter-reflections between surfaces play an important role, especially near the shadow boundary where the body reflection component is very weak.