Empirical Evaluation of Crowds Using Automated Methods

Muhammad Baqui (), Michelle Isenhour () and Rainald Löhner ()
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Muhammad Baqui: George Mason University
Michelle Isenhour: Naval Post Graduate School
Rainald Löhner: George Mason University

A chapter in Traffic and Granular Flow '17, 2019, pp 143-150 from Springer

Abstract: Abstract This work presents a novel framework for automated monitoring of high density crowds from closed circuit television (CCTV) image data. The framework obtains pedestrian velocities from particle image velocimetry (PIV) technique and densities from a boosted ferns machine learning model. A pinhole camera based perspective correction scheme is employed to convert the 2D pixel coordinates into 3D metric coordinates. The framework is trained with and tested against real-world event data from the Hajj.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-11440-4_17

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DOI: 10.1007/978-3-030-11440-4_17

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