The generic viewpoint assumption in a Bayesian framework

The g̈eneric vieẅassumption states that an observer is not in a special position relative to the scene. It is commonly used to disqualify scene interpretations that assume special viewpoints, following a binary decision that the viewpoint was either generic or accidental. In this chapter, we show how to use the generic view assumption to quantify the likelihood of a view. This quantitative approach can be applied to estimate scene parameters. This approach applies to many vision problems. We show shape from shading examples where we rank shapes or reflectance functions in cases which are otherwise ambiguous. The rankings agree with the perceived values. Bayesian Perspectives on Perception, David Knill and Whitman Richards, editors, Cambridge University Press, 1996 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Research Laboratories, Inc.; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Research Laboratories, Inc. All rights reserved. Copyright c ©Mitsubishi Electric Research Laboratories, Inc., 1994 201 Broadway, Cambridge, Massachusetts 02139