Crowd monitoring using computer vision

Ryan, David Andrew (2014) Crowd monitoring using computer vision. PhD thesis, Queensland University of Technology.


Novel computer vision techniques have been developed for automatic monitoring of crowed environments such as airports, railway stations and shopping malls. Using video feeds from multiple cameras, the techniques enable crowd counting, crowd flow monitoring, queue monitoring and abnormal event detection. The outcome of the research is useful for surveillance applications and for obtaining operational metrics to improve business efficiency.

Impact and interest:

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783 since deposited on 08 Jan 2014
249 in the past twelve months

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ID Code: 65652
Item Type: QUT Thesis (PhD)
Supervisor: Sridharan, Sridha, Fookes, Clinton, & Denman, Simon
Keywords: Crowd Monitoring, Crowd Counting, Crowd Flow, Queue Monitoring, Anomaly Detection, Local Features, Scene Invariant, Multi Camera, Virtual Gate, Textures of Optical Flow
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > Institutes > Institute for Future Environments
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Institution: Queensland University of Technology
Deposited On: 08 Jan 2014 23:45
Last Modified: 07 Sep 2015 01:00

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