ABSTRACT
Abstract-A growing trend in com puter vision has been the use of physical reflectance models, predicting reflected radiant intensity and color, to obtain constraints on object features. Until recently, relatively little attention has been paid to analysis of the reflected polarization state of light and what feature constraints this might provide to an automated vision system. Even though there is no analogy with human vision, we dem onstrate that a wealth of constraint information can be obtained by resolving polarization components of reflected light with a polarizing filter placed in front of a camera sensor. We present a polarization re flectance model known as the F resnel reflectance model because of its use of the Fresnel reflection coefficients. This reflectance model accurately predicts the magnitudes of polarization components of reflected light, and all the polarization-based methods presented in this paper follow from this model.
