Inferences from Images: Final Report 1984-1987

Abstract

How can a visual system make reliable inferences about surface properties? To answer such questions, one can use computer graphics to generate a realistic rendition of a surface, such as water, clouds or rock. Such a rendition demonstrates that all the relevent psychophysical parameters have been indentified. Given these parameters, or rather their image correlates, we then proceed to show how the surface type can be inferred from the available image information (inverse optics). The surface we have studied most extensively is water, including some of its dynamical properties. Certain aspects of the motion of planar surfaces were also investigated. Our results suggest a simplification of the Cook-Torrance model for the reflection function. Keywords: Vision; Visual perception; Motion; Material type; Water; Computer graphics; Machine vision; Short-long wave interaction; Acoustics; Sound perception; Reflectance function.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1988
Accession Number
ADA210710

Entities

People

  • Shimon Ullman
  • Whitman Richards

Organizations

  • Massachusetts Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Cognitive Science
  • Computational Science
  • Computer Graphics
  • Computer Vision
  • Coordinate Systems
  • Distribution Functions
  • Lepidoptera
  • Linear Systems
  • Mechanics
  • Optics
  • Psychology
  • Refractive Index
  • Three Dimensional
  • Two Dimensional
  • Vibration
  • Waveforms

Readers

  • Computer Vision.
  • Systems Analysis and Design
  • Wave Propagation and Nonlinear Chaotic Dynamics.

Technology Areas

  • AI & ML