Extracting Crowd Velocities at High Density

Muhammad Baqui, Rainald Löhner

Abstract


Velocity is a fundamental property of foot traffic flow. Monitoring the change of velocity patterns at high pedestrian densities may provide valuable insights on foot traffic dynamics. In this paper, a closer look is taken to explore the capability of the Particle Image Velocimetry (PIV) technique on extracting crowd velocities from surveillance camera images. Experiments are performed to report the accuracy of pedestrian velocity extraction with PIV. Quantitative accuracy is reported with manual tracking of pedestrians, surveying correlation misses at different window sizes and compute times. The results indicate that the PIV algorithm can be a good candidate for velocity extraction in real-time.

Keywords


particle image velocimetry (piv); crowd monitoring; pedestrian flow; surveillance

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DOI: http://dx.doi.org/10.17815/CD.2020.110

Copyright (c) 2020 Muhammad Baqui, Rainald Löhner

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