Traffic congestion classification for nighttime surveillance videos

Hua Tsung Chen*, Li Wu Tsai, Hui Zhen Gu, Suh Yin Lee, Bao-Shuh Lin 

*Corresponding author for this work

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

11 Scopus citations

Abstract

Traffic surveillance systems have been widely used for traffic monitoring. If the degree of traffic congestion can be evaluated from the surveillance videos immediately, the drivers can choose alternate routes to avoid traffic jam when traffic congestion arises. Compared to daytime surveillance, some tough factors such as poor visibility and higher noise increase the difficulty in video understanding under nighttime environments. In this paper, we propose a framework of traffic congestion classification for nighttime surveillance videos. The framework consists of three steps: the first one is to detect headlights based on three salient headlight features. Second, headlights are grouped into individual vehicles by evaluating their correlations. Third, a virtual detection line is adopted to gather the traffic information for traffic congestion evaluation. Then the traffic congestion is classified into five levels: jam, heavy, medium, mild and low in real-time. We use freeway nighttime surveillance videos to demonstrate the performances on accuracy and computation. Satisfactory experimental results validate the effectiveness of the proposed framework.

Original languageEnglish
Title of host publicationProceedings of the 2012 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2012
Pages169-174
Number of pages6
DOIs
StatePublished - 4 Oct 2012
Event2012 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2012 - Melbourne, VIC, Australia
Duration: 9 Jul 201213 Jul 2012

Publication series

NameProceedings of the 2012 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2012

Conference

Conference2012 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2012
CountryAustralia
CityMelbourne, VIC
Period9/07/1213/07/12

Keywords

  • headlight detection
  • nighttime surveillance
  • traffic congestion
  • virtual detection line

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