Tracking all traffic

Computer vision algorithms for monitoring vehicles individuals, and crowds

Benjamin Maurin, Osama Masoud, Nikolaos P Papanikolopoulos

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

A vision-based system for monitoring crowded urban scenes is proposed. The approach combines an effective detection scheme based on optical flow and background removal that can locate vehicles, individual pedestrians, and crowds. The detection phase is followed by the tracking phase that tracks all the detected entities. Potential applications include intersection control, traffic data collection, and even crowd control after athletic events.

Original languageEnglish (US)
Pages (from-to)29-36
Number of pages8
JournalIEEE Robotics and Automation Magazine
Volume12
Issue number1
DOIs
StatePublished - Mar 1 2005

Fingerprint

Optical flows
Traffic control
Computer vision
Monitoring

Keywords

  • Computer vision algorithms
  • Crowds
  • Intersections
  • Monitoring systems
  • Tracking schemes
  • Traffic objects
  • Vision-based system

Cite this

Tracking all traffic : Computer vision algorithms for monitoring vehicles individuals, and crowds. / Maurin, Benjamin; Masoud, Osama; Papanikolopoulos, Nikolaos P.

In: IEEE Robotics and Automation Magazine, Vol. 12, No. 1, 01.03.2005, p. 29-36.

Research output: Contribution to journalArticle

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