Visual tracking strategies for intelligent vehicle-highway systems

Christopher E. Smith, Nikolaos P. Papanikolopoulos, Scott A. Brandt, Charles Richards

Research output: Contribution to journalConference article

3 Scopus citations

Abstract

The complexity and congestion of current transportation systems often produce traffic situations that jeopardize the safety of the people involved. These situations vary from maintaining a safe distance behind a leading vehicle to safely allowing a pedestrian to cross a busy street. Environmental sensing plays a critical role in virtually all of these situations. Of the sensors available, vision sensors provide information that is richer and more complete than other sensors, making them a logical choice for a multisensor transportation system. In this paper we present robust techniques for intelligent vehicle-highway applications where computer vision plays a crucial role. In particular, we demonstrate that the Controlled Active Vision framework1 can be utilized to provide a visual sensing modality to a traffic advisory system in order to increase the overall safety margin in a variety of common traffic situations. We have selected two application examples, vehicle tracking and pedestrian tracking, to demonstrate that the framework can provide precisely the type of information required to effectively manage the given situation.

Original languageEnglish (US)
Pages (from-to)234-245
Number of pages12
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume2344
DOIs
StatePublished - Dec 29 1994
EventIntelligent Vehicle Highway Systems 1994 - Boston, United States
Duration: Oct 31 1994Nov 4 1994

    Fingerprint

Keywords

  • Detection
  • Intelligent vehicle-highway systems
  • Optical flow
  • Pedestrian control
  • Visual tracking

Cite this