Much of this research continues the development of the fundamentals of Polarization Vision for image understanding which the principal investigator initiated as a doctoral student. This research also continues the development of Polarization Cameras which are a new class of sensors that automatically sense polarization and compute either a visualization of polarization information, or, properties of a scene that are physically related to polarization. The additional physical dimensions of polarization of light beyond that of intensity, carry extra information from a scene that can provide a richer set of descriptive physical constraints for the understanding of images. Past work by the principal investigator has revealed Polarization Vision techniques that can be used to perform dielectric/metal material identification, specular and diffuse reflection component separation and analysis, as well as complex image segmentations that would be immensely more complicated or even infeasible using intensity and color information alone. A new intensity diffuse reflectance model has been formally developed for smooth dielectric surfaces that generalizes Lambert's Law. Implications of this more accurate diffuse reflectance model are being studied for 3-D shape recovery from reflectance in computer vision. New techniques are being developed for 3-D shape recovery from binocular stereo using correspondence of photometric values.
