Research in Knowledge-Based Vision Techniques for the Autonomous Land Vehicle Program

Abstract

This report describes our research in motion analysis and estimation techniques. This research is of particular relevance to the DARPA Autonomous Land Vehicle (ALV) program, but should also be of other general utility. Our basic approach detecting and tracking motion is to extract and match features, such as lines and regions, from a sequence and to generate emotion estimates from these. We present one report on matching edge elements in connected line segments (contours) in a sequence of views. This work assumes relatively small motions between views. We also present a report on an alternative representation for motion and a technique to use occlusion in spatio-temporal analysis. We also present results from a basic integrated system that combines feature extraction, matching and motion estimation. Keywords: Target detection knowledge-based vision.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1988
Accession Number
ADA208546

Entities

People

  • G. Medioni
  • K. Price
  • R. Nevatia
  • S. Gazit
  • W. Franzen

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Biomedical
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Collision Avoidance
  • Computer Graphics
  • Computer Languages
  • Computer Vision
  • Coordinate Systems
  • Detection
  • Detectors
  • Feature Extraction
  • Image Processing
  • Information Processing
  • Information Science
  • Machine Perception
  • Pattern Recognition
  • Recognition
  • Three Dimensional
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Computer Vision.

Technology Areas

  • AI & ML