SYMBOLIC TRAFFIC SCENE ANALYSIS USING DYNAMIC BELIEF NETWORKS

This paper addresses the subject of traffic scene analysis. It describes the operations that take place from the low-level processing of a traffic scene to its high-level description. It explains what dynamic belief networks are and some issues involved in using them for scene analysis. It describes a small traffic situation and how a dynamic belief network could represent it. It concludes with a short summary of future work on this topic.

• Supplemental Notes:
  • Publication Date: 1993 Published By: Institute of Transportation Studies, University of California, California PATH, Berkeley, Calif.
• Corporate Authors:

  University of California, Berkeley

  California PATH Program, Institute of Transportation Studies
  Richmond Field Station, 1357 South 46th Street
  Richmond, CA  United States  94804-4648

  University of California, Berkeley

  Department of Electrical Engineering and Computer Sciences
  Berkeley, CA  United States  94720

  California Department of Transportation

  1120 N Street
  Sacramento, CA  United States  95814
• Authors:
  • Huang, Tim
  • Ogasawara, Gary
  • Russell, Stuart
• Publication Date: 1993

Language

• English

Media Info

• Pagination: 5 p.
• Serial:
  • PATH Technical Memorandum ; 93-8
  • Publisher: University of California, Berkeley

Subject/Index Terms

• TRT Terms: Computer vision; Intelligent transportation systems; Traffic flow; Traffic surveillance
• Subject Areas: Operations and Traffic Management;

Filing Info

• Accession Number: 00785219
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Report/Paper Numbers: PATH Technical Memorandum 93-8
• Files: PATH, STATEDOT
• Created Date: Nov 17 2000 12:00AM