Robust Vehicle Detector Using Spatio-Temporal MRF Model

Nowadays, cameras set on highways and local streets are broadly used in traffic measurements and monitoring systems. Traffic measurement plays an important role in ITS (intelligent transportation systems), which can provide congestion and travel time information for drivers. However, traditional methods suffered the problem of occlusion and illumination effects. In this paper, a novel vehicle detector is introduced and the experiment results show that the authors vehicle detector performs robustly under various environmental conditions. In the authors vehicle detector, based on the high performance of vehicle tracking, the traffic flow of each lane and velocity of each vehicle can be calculated precisely. As for the vehicle tracking, the ST-MRF model is used which is very effective even in circumstances of occlusion and illumination change. Considering low illumination conditions at night, a tail lamp extraction algorithm is developed for vehicle detection. Experiments under various conditions show that our vehicle detector achieved a detection rate of 97.9% in total.

• Supplemental Notes:
  • Abstract reprinted with permission from Intelligent Transportation Society of America.
• Corporate Authors:

  ITS America

  1100 17th Street, NW, 12th Floor
  Washington, DC  United States  20036
• Authors:
  • Ushirogohchi, Daisuke
  • Sakamoto, Yoshihiro
  • Kajitani, Koichiro
  • Naito, Takeshi
  • Kamijo, Shunsuke
• Conference:
  • 19th ITS World Congress
  • Location: Vienna , Austria
  • Date: 2012-10-22 to 2012-10-26
• Publication Date: 2012

Language

• English

Media Info

• Media Type: Digital/other
• Features: CD-ROM; Figures; Photos; References; Tables;
• Pagination: 8p
• Monograph Title: 19th ITS World Congress, Vienna, Austria, 22 to 26 October 2012

Subject/Index Terms

• TRT Terms: Cameras; Intelligent transportation systems; Traffic congestion; Traffic flow; Traffic surveillance; Travel time; Vehicle detectors
• Subject Areas: Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control;

Filing Info

• Accession Number: 01499002
• Record Type: Publication
• Files: TRIS
• Created Date: Nov 21 2013 9:14AM