Computational Vision Model (CVM) Research and Development

Abstract

In the present effort, we have built a new and improved model for the prediction of target acquisition. It is based on the latest models of early vision processes in the human visual system. It is a multi-channel model, based on three color opponent channels, and two temporal channels. Each channel is further subdivided into a set of multi-resolution channels. Computations are based on contrast ratio. Local energy values for these dimensionless contrast images are computed, and normalized by the sum of eye noise and clutter. The detectability metric is then computed from these energies. This model has been applied to the problem of detecting cars approaching intersections, and to the detection of mobile ground targets in imagery taken from an airborne first generation FLIR system. Reasonably good correlations were obtained. Several alternative studies were also undertaken, along with a critique, in hindsight, of the ideas and philosophy used in the development of the model.

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Document Details

Document Type
Technical Report
Publication Date
Mar 13, 1998
Accession Number
ADA361237

Entities

People

  • Allyn W. Dunstan
  • Goerge H. Lindquist
  • J. Richard Freeling

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies
  • Human Systems
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Channel Models
  • Cognition
  • Computations
  • Computer Programs
  • Computer Vision
  • Detection
  • Detectors
  • Geometry
  • Image Processing
  • Information Processing
  • Neural Pathways
  • Pattern Recognition
  • Perception
  • Psychology
  • Signal Processing
  • Three Dimensional

Readers

  • Computational Modeling and Simulation
  • Military History of the United States in the 20th Century.
  • Radar Systems Engineering.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference