Video Detection and Classification of Pedestrian Events at Roundabouts and Crosswalks
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Video Detection and Classification of Pedestrian Events at Roundabouts and Crosswalks
Published Date
2013-08
Publisher
Intelligent Transportation Systems Institute, Center for Transportation Studies
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Report
Abstract
A well-established technique for studying pedestrian safety is based on reducing data from video-based in-situ
observation. The extraction and cataloging from recorded video of pedestrian crossing events has largely been
achieved manually. Although the manual methods are generally reliable, they are extremely time-consuming. As a
result, more detailed, encompassing site studies are not practical unless the mining for these events can be
automated. The study investigated such a tool based on utilizing a novel image processing algorithm recently
developed for the extraction of human activities in complex scenes. No human intervention other than defining
regions of interest for approaching vehicles and the pedestrian crossing areas was required. The output quantified
general event indicators—such as pedestrian wait time, and crossing time and vehicle-pedestrian yield behaviors.
Such data can then be used to guide more detailed analyses of the events to study potential vehicle-pedestrian
conflicts and their causal effects. The evaluation was done using an extensive set of multi-camera video recordings
collected at roundabouts. The tool can be used to support other pedestrian safety research where extracting potential
pedestrian-vehicle conflicts from video are required, for example at crosswalks at urban signalized and
uncontrolled intersections.
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Intelligent Transportation Systems Institute, Center for Transportation Studies
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Morris, Ted; Li, Xinyan; Morellas, Vassilios; Papanikolopoulos, Nikos. (2013). Video Detection and Classification of Pedestrian Events at Roundabouts and Crosswalks. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/159158.
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