Estimating Relative Vehicle Motions in Traffic Scenes

Abstract

Autonomous operation of a vehicle on a road calls for understanding of various events involving the motions of the vehicles in its vicinity. In this paper we show how a moving vehicle which is carrying a camera can estimate the relative motions of nearby vehicles. We present a model for the motion of the observing vehicle, and show how to 'stabilize' it, i.e. to correct the image sequence so that transient motions resulting from bumps, etc. are removed and the sequence corresponds more closely to the sequence that would have been collected if the motion had been smooth. We also model the motions of nearby vehicles and show how to detect their motions relative to the observing vehicle. We present results for several road image sequences which demonstrate the effectiveness of our approach.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1998
Accession Number
ADA341959

Entities

People

  • Ehud Rivlin
  • Roman Goldenberg
  • Zoran Duric

Organizations

  • University of Maryland

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • C4I
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Cartesian Coordinates
  • Computational Science
  • Computer Science
  • Computer Vision
  • Coordinate Systems
  • Detection
  • Equations
  • Equations Of Motion
  • Flow Fields
  • Ground Vehicles
  • Pattern Recognition
  • Recognition
  • Relative Motion
  • Sequences
  • Two Dimensional

Fields of Study

  • Computer science

Readers

  • Control Systems Engineering.
  • Sensor Fusion and Tracking Systems.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.