Reflectance estimation in the presence of sharp shadows or transparency

Daniel Kersten, Daniel J. Plummer

Research output: Contribution to journalConference articlepeer-review

Abstract

Human observers can reliably and accurately estimate the reflectance of surfaces in the presence of either strongly visible multiplicative illumination, or additive veiling light. In the presence of sufficient information about scene layout, this ability is only mildly affected by the sharpness of a shadow, and remains intact for sharp transparent overlays and spotlights. Using a Bayesian approach, the authors have sought to explore optimal limits to this ability. The first step is to construct the posterior probability of the reflectance and illumination maps conditional on the image. The second step is to locate a maximum, preferably the global maximum, of the posterior probability. In the final step, the authors compare the simulations to human estimation and perception of reflectance in a world of piece-wise constant reflectances and illuminants.

Original languageEnglish (US)
Number of pages1
JournalNeural Networks
Volume1
Issue number1 SUPPL
DOIs
StatePublished - Jan 1 1988
EventInternational Neural Network Society 1988 First Annual Meeting - Boston, MA, USA
Duration: Sep 6 1988Sep 10 1988

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