Digital Signal Processing


Recognition and Tracking Analytics for Crowd Control

Authors: Abbad Vakil, Saransh Kacharia, Brian Liao, Haytham Shaban, Ibrahim Mohiuddin

We explore and apply methods of image analization in several forms in order to monitor the condition and health of a crowd. Stampedes, congestion, and traffic all occur as a result of inefficient crowd management. Our software identifies congested areas and determines solutions to avoid congestion based on live data. The data is then processed by a local device which is fed via camera. This method was tested in simulation and proved to create a more efficient and congestion-free scenario. Future plans include depth sensing for automatic calibration and suggested course of action.

Comments: 15 Pages.

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Submission history

[v1] 2016-09-01 23:12:12

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