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Performance Evaluation of Video Analytics for Traffic Incident Detection and Vehicle Counts Collection

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 121 ))

Abstract

Current incident detection and traffic monitoring method using closed-circuit television (CCTV) cameras meets with limitations as the coverage of CCTV cameras rapidly expands. In general, traffic operators at Traffic Operation Center (TOC) have to manage and monitor numerous CCTV cameras 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 show that the performance of video analytics is significantly impacted by video quality and other environmental factors such as lighting and weather conditions.

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Correspondence to Kitae Kim .

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Kim, K. et al. (2017). Performance Evaluation of Video Analytics for Traffic Incident Detection and Vehicle Counts Collection. In: Liu, C. (eds) Recent Advances in Intelligent Image Search and Video Retrieval. Intelligent Systems Reference Library, vol 121 . Springer, Cham. https://doi.org/10.1007/978-3-319-52081-0_9

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  • DOI: https://doi.org/10.1007/978-3-319-52081-0_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52080-3

  • Online ISBN: 978-3-319-52081-0

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