Mechanisms for the Perception of Surface Qualities

Massachusetts Institute Of Technology, Cambridge MA

Investigators

Abstract

Even the best computer vision system falls far short of human vision. A person has no problem recognizing metal as metal or wood as wood. These are examples of material perception in which vision relies on combinations of color, texture, transparency, and glossiness to recognize the material surface of objects. With NSF Support Dr. Edward Adelson studies how perception puts information together, thereby allowing material perception. His working hypothesis is that human vision relies on certain statistical relationships between colors and patterns within an image, and uses these to infer the material. However, the exact nature of these relationships remains to be understood. Broader impacts of the research are important in everyday life. People care greatly about the appearance of their skin and hair, the clothing they wear, and the food they eat. If we can understand the principles that determine material perception, it will help industrial researchers who seek to make new products with improved surface appearance, such as new kinds of cosmetics or paint. An understanding of material perception may also pay off in better machine vision systems. For instance, an automated vehicle should be able to distinguish pavement, dirt, mud, or ice and adjust its driving accordingly, but today's machine vision systems find such problems quite difficult. By emulating the mechanisms of human vision, we can develop more powerful machine vision systems.