Performance evaluation of video analytics for traffic incident detection and vehicle counts collection

Kitae Kim, Slobodan Gutesa, Branislav Dimitrijevic, Joyoung Lee, Lazar Spasovic, Wasif Mirza, Jeevanjot Singh

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Current incident detection and traffic monitoring method using closedcircuit television (CCTV) cameras meets with limitations as the coverage of CCTV cameras rapidly expands. In general, traffic operators at Traffic Operation Center (TOC) have tomanage and monitor numerousCCTVcameras deployed on roadways. Thus, many transportation agencies consider the use of video analytics system to reduce incident detection time and minimize traffic impacts, but they also want to validate the performance of the video analytics system whether it can work with their existing video surveillance infrastructure before procuring the system. To that end, a pilot study was designed and conducted to evaluate the accuracy of a video analytics product by integrating with CCTV cameras deployed on highways. The pilot study was designed to evaluate the accuracy of video analytics in detecting incidents and collecting traffic counts. The test results showthat the performance of video analytics is significantly impacted by video quality and other environmental factors such as lighting and weather conditions.

Original languageEnglish (US)
Title of host publicationIntelligent Systems Reference Library
PublisherSpringer Science and Business Media Deutschland GmbH
Pages213-231
Number of pages19
DOIs
StatePublished - Jan 1 2017

Publication series

NameIntelligent Systems Reference Library
Volume121
ISSN (Print)1868-4394
ISSN (Electronic)1868-4408

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Information Systems and Management
  • Library and Information Sciences

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