1 April 1991 Shape-from-X: psychophysics and computation
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Proceedings Volume 1383, Sensor Fusion III: 3D Perception and Recognition; (1991); doi: 10.1117/12.25259
Event: Advances in Intelligent Robotics Systems, 1990, Boston, MA, United States
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.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Heinrich H. Buelthoff, Alan L. Yuille, "Shape-from-X: psychophysics and computation", Proc. SPIE 1383, Sensor Fusion III: 3D Perception and Recognition, (1 April 1991); doi: 10.1117/12.25259; https://doi.org/10.1117/12.25259
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KEYWORDS
Sensor fusion

Transparency

Fusion energy

Stereo holograms

Eye

Opacity

3D modeling

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