Browsing Artificial Intelligence Lab Publications by Author "Adelson, Edward H."
Now showing items 1-6 of 6
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How do Humans Determine Reflectance Properties under Unknown Illumination?
Fleming, Roland W.; Dror, Ron O.; Adelson, Edward H. (2001-10-21)Under normal viewing conditions, humans find it easy to distinguish between objects made out of different materials such as plastic, metal, or paper. Untextured materials such as these have different surface reflectance ... -
The Perceptual Buildup of Three-Dimensional Structure from Motion
Hildreth, Ellen C.; Grzywacz, Norberto M.; Adelson, Edward H.; Inada, Victor K. (1989-08-01)We present psychophysical experiments that measure the accuracy of perceived 3D structure derived from relative image motion. The experiments are motivated by Ullman's incremental rigidity scheme, which builds up 3D ... -
Recovering Intrinsic Images from a Single Image
Tappen, Marshall F.; Freeman, William T.; Adelson, Edward H. (2002-09-01)We present an algorithm that uses multiple cues to recover shading and reflectance intrinsic images from a single image. Using both color information and a classifier trained to recognize gray-scale patterns, each image ... -
Separating Reflections from Images Using Independent Components Analysis
Farid, Hany; Adelson, Edward H. (1998-09-01)The image of an object can vary dramatically depending on lighting, specularities/reflections and shadows. It is often advantageous to separate these incidental variations from the intrinsic aspects of an image. Along these ... -
Slow and Smooth: A Bayesian Theory for the Combination of Local Motion Signals in Human Vision
Weiss, Yar; Adelson, Edward H. (1998-02-01)In order to estimate the motion of an object, the visual system needs to combine multiple local measurements, each of which carries some degree of ambiguity. We present a model of motion perception whereby measurements ... -
Surface Reflectance Estimation and Natural Illumination Statistics
Dror, Ron O.; Adelson, Edward H.; Willsky, Alan S. (2001-09-01)Humans recognize optical reflectance properties of surfaces such as metal, plastic, or paper from a single image without knowledge of illumination. We develop a machine vision system to perform similar recognition tasks ...