Special Section on Video Analytics for Public Safety

Investigation of safety analysis methods using computer vision techniques

[+] Author Affiliations
Mohammad Shokrolah Shirazi

Cleveland State University, Electrical Engineering and Computer Science Department, Cleveland, Ohio, United States

Brendan Tran Morris

University of Nevada, Las Vegas, Electrical and Computer Engineering Department, Las Vegas, Nevada, United States

J. Electron. Imaging. 26(5), 051404 (Jun 14, 2017). doi:10.1117/1.JEI.26.5.051404
History: Received January 20, 2017; Accepted April 28, 2017
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Abstract.  This work investigates safety analysis methods using computer vision techniques. The vision-based tracking system is developed to provide the trajectory of road users including vehicles and pedestrians. Safety analysis methods are developed to estimate time to collision (TTC) and postencroachment time (PET) that are two important safety measurements. Corresponding algorithms are presented and their advantages and drawbacks are shown through their success in capturing the conflict events in real time. The performance of the tracking system is evaluated first, and probability density estimation of TTC and PET are shown for 1-h monitoring of a Las Vegas intersection. Finally, an idea of an intersection safety map is introduced, and TTC values of two different intersections are estimated for 1 day from 8:00 a.m. to 6:00 p.m.

© 2017 SPIE and IS&T

Citation

Mohammad Shokrolah Shirazi and Brendan Tran Morris
"Investigation of safety analysis methods using computer vision techniques", J. Electron. Imaging. 26(5), 051404 (Jun 14, 2017). ; http://dx.doi.org/10.1117/1.JEI.26.5.051404


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