Foveal Machine Vision Systems

Abstract

This work presents a new class of active machine vision systems, called foveal machine vision systems, which feature space variant sampling directed by gaze strategies. Two families of space variant sampling geometries are analyzed with spatial resolution decreasing with distance from the optical axis. One family features a linear acuity roll-off, and the other an exponential roll-off. Techniques are presented for the integration of sensor frames into unified static scene perceptions. Foveal systems can use many existing hierarchical processing techniques, in particular image pyramid structures and algorithms. A hierarchical structure called the foveal polygon is described. The foveal polygon is the subset of an image pyramid supported by foveal sensor frame. Top-down (coarse-to-fine) algorithms processing polygon data serve as drivers for gaze control. Additional gaze control strategies are presented for general learning and surveying (minimization of hypothesis entropy), and feature interrogation (hypothesis likelihood maximization).

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1990
Accession Number
ADA226274

Entities

People

  • Cesar Bandera

Tags

Communities of Interest

  • Energy and Power Technologies
  • Human Systems
  • Sensors
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Computational Science
  • Computer Programming
  • Computer Vision
  • Control Systems
  • Data Processing
  • Detection
  • Detectors
  • Image Processing
  • Information Science
  • Infrared Detectors
  • Neural Networks
  • Parallel Computing
  • Signal Processing
  • Three Dimensional
  • Two Dimensional
  • Warning Systems

Readers

  • Computer Vision.
  • Graph Algorithms and Convex Optimization.
  • Military/Explosive Ordnance Disposal (EOD) Technology

Technology Areas

  • Space
  • Space - Space Objects
  • Space - Spacecraft Maneuvers