Human Image Understanding

Abstract

This report summarizes the major research accomplishments performed under AFOSR Grant 88-0231, HUMAN IMAGE UNDERSTANDING. An extensive services of experiments assessing the visual priming of briefly presented images indicate that the visual representation that mediates real time object recognition specifies neither the image edges or vertices nor an overall model of the object but an arrangement of simple volumes (or geons) corresponding to the object's parts. This representation can be activated with no loss in efficiency when the image is projected onto the retina at another position, size, or orientation in depth from when originally viewed. Consideration of these invariances suggests a computational basis for the evolution of two extrastriate visual systems, one for recognition and the other subserving motor interaction. It may be possible to assess the functioning of these systems behaviorally, that is, to split the cortex horizontally, through a comparison of performance on naming and episodic memory tasks. We have developed a neural network model (Hummel and Biederman, 1992) that captures the essential characteristics of human object recognition performance.

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Document Details

Document Type
Technical Report
Publication Date
Apr 17, 1992
Accession Number
ADA250401

Entities

People

  • Irving Biederman

Organizations

  • University of Minnesota

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Artificial Intelligence Software
  • Brain
  • Cognitive Science
  • Computer Science
  • Computer Vision
  • Image Recognition
  • Information Systems
  • Military Research
  • Neural Networks
  • Neurosciences
  • Object Recognition
  • Pattern Recognition
  • Psychology
  • Recognition
  • Three Dimensional

Fields of Study

  • Computer science

Readers

  • Business Analytics
  • Computer Vision.
  • Neuroscience

Technology Areas

  • AI & ML