Recovering reflectance and illumination in a world of painted polyhedra

To be immune to variations in illumination, a vision system needs to be able to decompose images into their illumination and surface reflectance components. Most computational studies thus far have been concerned with strategies for solving the problem in the restricted domain of 2-D Mondrians. This domain has the simplifying characteristic of permitting discontinuities only in the reflectance distribution while the illumination distribution is constrained to vary smoothly. Such approaches prove inadequate in a 3-D world of painted polyhedra which allows for the existence of discontinuities in both the reflectance and illumination distributions. The authors propose a two-stage computational strategy for interpreting images acquired in such a domain. The first stage attempts to use simple local gray-level junction analysis to classify the observed image edges into the illumination or reflectance categories. Subsequent processing verifies the global consistency of these local inferences while also reasoning about the 3-D structure of the object and the illumination source direction