Current problems in lightness theory

Rutgers University Newark, Newark NJ

Investigators

Abstract

The two leading theories of how the white/gray/black shade of a surface is computed in your brain will be tested against each other in a series of 10 experiments. Human observers will be presented with three-dimensional displays carefully constructed so that, under controlled viewing conditions, the two theories make different predictions regarding the gray shade that will be perceived for a test surface embedded within the display. All of the displays will incorporate a serious challenge for vision, namely, multiple areas of light and shadow. These displays will vary in terms of (a) whether the change of illumination is projected onto a surface or occurs at a corner (or bend) in the surface, (b) the number of different gray shades on each surface, and (c) the range of gray shades on a given surface. The observers will be asked to match critical parts of each display for gray level and level of illumination. The strengths and weaknesses of each of the theories will be evaluated based on the observer matches. Ideally these results will suggest how the respective strengths of the two theories might be integrated. How humans see the white, gray, and black shade of objects has not yet been explained scientifically. The basic problem is that the light that an object reflects to the eye does not reveal the shade of the object because it depends so heavily on the intensity of illumination on the object. Thus any intensity of light can be reflected from any shade of gray. The problem can only be solved by analyzing the surrounding context. Advances in our understanding of the nature of this analysis are absolutely necessary for guiding brain research in this area. The work will impact computer vision as well. At the moment, no robot can simply look at an object and report its shade of gray. Work with human vision provides the best hope for making better computer programs. Ironically, the proposed work will be conducted, not using computer images, as is almost universally done in human vision research, but with actual three-dimensional displays that are far more realistic.