Safety Quantification of Intersections Using Computer Vision Techniques
Vision-based safety analysis is a difficult task since traditional motion-based techniques work poorly when pedestrians and vehicles stop due to traffic signals. This work presents a tracking method in order to provide a robust tracking of pedestrians and vehicles, and quantify safety through investigating the tracks. Surrogate safety measurements are estimated including TTC and DTI values for a highly cluttered video of Las Vegas intersection and the performance of the tracking system is evaluated at detection and tracking steps separately.
KeywordsBipartite Graph Optical Flow Gaussian Mixture Model Local Binary Pattern Traffic Signal
The authors acknowledge the Nevada Department of Transportation for their support of this research.
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