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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|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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