Automatic Traffic Surveillance System for Vehicle Tracking and Classification

In this paper, the authors propose a novel automatic traffic surveillance system designed to detect, track, and recognize vehicles from various video sequences. Using only one camera, the proposed method is able to categorize vehicles into more specific classes through a new linearity feature in vehicle representation. The proposed system can also handle the problem of vehicle occlusions caused by shadows using a novel line-based shadow elimination algorithm. Finally, the proposed system also features an automatic method for detecting lane-dividing lines, which can ultimately enhance the accuracy of vehicle classification.

• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/oclc/41297384
• Authors:
  • Hsieh, Jun-Wei
  • Yu, Shih-Hao
  • Chen, Yung-Sheng
  • Hu, Wen-Fong
• Publication Date: 2006-6

Language

• English

Media Info

• Media Type: Print
• Features: Figures; References; Tables;
• Pagination: pp 175-187
• Serial:
  • IEEE Transactions on Intelligent Transportation Systems
  • Volume: 7
  • Issue Number: 2
  • Publisher: Institute of Electrical and Electronics Engineers (IEEE)
  • ISSN: 1524-9050
  • Serial URL: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6979

Subject/Index Terms

• TRT Terms: Automatic vehicle classification; Automatic vehicle detection and identification systems; Lane lines; Traffic surveillance; Vehicle classification; Vehicle detectors
• Subject Areas: Highways; Operations and Traffic Management; I70: Traffic and Transport;

Filing Info

• Accession Number: 01055794
• Record Type: Publication
• Source Agency: UC Berkeley Transportation Library
• Files: BTRIS, TRIS
• Created Date: Aug 20 2007 5:42PM