Vehicle tracking in daytime and nighttime traffic surveillance videos

Hsu Yung Cheng, Po Yi Liu, Yen Ju Lai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

In this work, a vehicle tracking system is developed to deal with daytime and nighttime traffic surveillance videos. For daytime videos, vehicles are detected via background modeling. For nighttime videos, headlights of vehicles need to be located and paired to initialize vehicles for the tracking purpose. An algorithm based on likelihood computation is developed to pair the headlights of vehicles. In addition, we apply a specialized system state transition model of the Kalman filter to adapt to common settings of traffic surveillance cameras. The experimental results have shown that the proposed method can effectively track vehicles in both daytime and nighttime surveillance videos. 2010 IEEE.

Original languageEnglish
Title of host publicationICETC 2010 - 2010 2nd International Conference on Education Technology and Computer
PagesV5122-V5125
DOIs
StatePublished - 2010
Event2010 2nd International Conference on Education Technology and Computer, ICETC 2010 - Shanghai, China
Duration: 22 Jun 201024 Jun 2010

Publication series

NameICETC 2010 - 2010 2nd International Conference on Education Technology and Computer
Volume5

Conference

Conference2010 2nd International Conference on Education Technology and Computer, ICETC 2010
Country/TerritoryChina
CityShanghai
Period22/06/1024/06/10

Keywords

  • Kalman filter
  • Tracking
  • Traffic surveillance

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