PedPIV: Pedestrian Velocity Extraction From Particle Image Velocimetry

The analysis of velocities from high-density pedestrian events may provide more information on pedestrian flow dynamics. A framework based on particle image velocimetry (PIV)-a technique commonly used in experimental fluid dynamics-has been developed to evaluate the pedestrian velocities from high-d...

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Bibliographic Details
Published in:IEEE transactions on intelligent transportation systems 2020-02, Vol.21 (2), p.580-589
Main Authors: Baqui, Muhammad, Lohner, Rainald
Format: Article
Language:English
Subjects:
Aerodynamics
Closed circuit television
Correlation
crowds management
Flow-density-speed relationships
Fluid dynamics
High density pedestrian flow
Legged locomotion
Mathematical model
Optical imaging
Optical sensors
Particle image velocimetry
Pedestrian traffic flow
pedestrian traffic management
pedestrian traffic planning
Pedestrians
Qualitative analysis
Security management
Television cameras
Tracking
Velocity measurement
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Summary:The analysis of velocities from high-density pedestrian events may provide more information on pedestrian flow dynamics. A framework based on particle image velocimetry (PIV)-a technique commonly used in experimental fluid dynamics-has been developed to evaluate the pedestrian velocities from high-density pedestrian events. The framework takes a sequence of two or more images from a regular closed-circuit television camera and obtains the flow properties (speed, direction) of the pedestrians. A detailed analysis has been done in both the qualitative and quantitative aspects of adapting PIV to pedestrian flow. An investigation through the use of the fundamental diagram and real-time extraction of crowd velocities is also presented and discussed. The proposed PIV-based framework enables on-the-spot analysis of pedestrian flow via velocity extraction in a reliable, automated manner.
ISSN:1524-9050
1558-0016
DOI:10.1109/TITS.2019.2899072