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Proceedings Paper

Shape-from-X: psychophysics and computation
Author(s): Heinrich H. Buelthoff; Alan L. Yuille
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Paper Abstract

The Bayesian approach to vision provides a fruitful theoretical framework for integrating different depth modules. In this formulation depth can be represented by one or more surfaces. Prior probabilities, corresponding to natural constraints, can be defined on these surfaces to avoid the ill-posedness of vision. We advocate strong coupling between different depth cues, so that the different modules can interact during computation. This framework is rich enough to accommodate straightforwardly both consonant and contradictory cue integration, by the use of binary decision units. These units can be interpreted in terms of robust statistics. A number of existing psychophysical experiments can be understood within this framework.

Paper Details

Date Published: 1 April 1991
PDF: 12 pages
Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25259
Show Author Affiliations
Heinrich H. Buelthoff, Brown Univ. (Germany)
Alan L. Yuille, Harvard Univ. (United States)


Published in SPIE Proceedings Vol. 1383:
Sensor Fusion III: 3D Perception and Recognition
Paul S. Schenker, Editor(s)

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