Human Image Understanding

Abstract

The goal of the effort is to develop and empirically evaluate a theory (Recognition-by-Components (RBC)) of real-time human target identification which assumes that objects are represented as an arrangement of simple generalized-cone volumes. The fundamental assumption of RBC is that a particular set of these convex components, called geons, can be derived from invariant properties of edges in a 2-D image. If an arrangement of three geons can be recovered from the input, objects can be quickly recognized even when they are occluded, rotated in depth, novel, extensively degraded, or embedded in a scene. The report describes the research on consequences of various forms of image degradation, the exploration of the role of surface features, the attentional demands of object recognition, formal modeling of object recognition, and extensions to scene perception and extensions to scene perception and expert identification. Keywords: Pattern recognition; Perception; Vision; Image understanding.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1989
Accession Number
ADA204490

Entities

People

  • Irving Biederman

Organizations

  • University at Buffalo

Tags

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Classification
  • Cognitive Science
  • Computational Processes
  • Computer Science
  • Computer Vision
  • Contrast
  • Curvature
  • Detection
  • Image Processing
  • Image Recognition
  • Object Recognition
  • Pattern Recognition
  • Perception
  • Psychology
  • Reaction Time
  • Simulations

Readers

  • Computer Vision.
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms