Real-time crowd safety and comfort management from CCTV images

Muhammad Baqui; Rainald Löhner

doi:10.1117/12.2262319

1 May 2017 Real-time crowd safety and comfort management from CCTV images

Muhammad Baqui, Rainald Löhner

Proceedings Volume 10223, Real-Time Image and Video Processing 2017; 1022304 (2017) https://doi.org/10.1117/12.2262319
Event: SPIE Commercial + Scientific Sensing and Imaging, 2017, Anaheim, CA, United States

Abstract

High density pedestrian flows are a common occurrence. Pedestrian safety and comfort in high density flows can present serious challenges to organizers, businesses and safety personnel. Obtaining pedestrian density and velocity directly from Closed Circuit Television (CCTV) would significantly improve real-time crowd management. A study of high density crowd monitoring from video and its real-time application viability is presented. The video data is captured from CCTV. Both cross correlation based and optical flow based approaches are studied. Results are presented in the form of fundamental diagrams, velocity vectors and speed contours of the flow field.

Conference Presentation

Citation Download Citation

Muhammad Baqui and Rainald Löhner "Real-time crowd safety and comfort management from CCTV images", Proc. SPIE 10223, Real-Time Image and Video Processing 2017, 1022304 (1 May 2017); https://doi.org/10.1117/12.2262319

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