Vision-based Bicycle/Motorcycle Classification

The authors present a feature-based classifier that distinguishes bicycles from motorcycles in real-world traffic scenes. The algorithm extracts some visual features focusing on the wheel regions of the vehicles. It splits the problem into two sub-cases depending on the computed motion direction. The classification is performed by non-linear Support Vector Machines. Tests lead to a successful vehicle classification rate of 96.7% on video sequences taken from different road junctions in an urban environment.

• Record URL:
  • https://doi.org/10.1016/j.patrec.2007.04.014
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/01678655
• Supplemental Notes:
  • Abstract reprinted with permission from Elsevier.
• Authors:
  • Messelodi, Stefano
  • Modena, Carla Maria
  • Cattoni, Gianni
• Publication Date: 2007-10

Language

• English

Media Info

• Media Type: Digital/other
• Features: Figures; Photos; Tables;
• Pagination: pp 1719-1726
• Serial:
  • Pattern Recognition Letters
  • Volume: 28
  • Issue Number: 13
  • Publisher: Elsevier
  • ISSN: 0167-8655

Subject/Index Terms

• TRT Terms: Bicycles; Image analysis; Motorcycles; Traffic surveillance; Vehicle classification
• Uncontrolled Terms: Support vector machines
• Subject Areas: Highways; Operations and Traffic Management; Pedestrians and Bicyclists; Planning and Forecasting; I72: Traffic and Transport Planning; I73: Traffic Control;

Filing Info

• Accession Number: 01360984
• Record Type: Publication
• Files: TRIS
• Created Date: Jan 25 2012 2:21PM