Large scale monitoring of crowds and building utilisation: A new database and distributed approach

Denman, Simon, Fookes, Clinton B., Ryan, David, & Sridharan, Sridha (2015) Large scale monitoring of crowds and building utilisation: A new database and distributed approach. In 12th IEEE International Conference on Advanced Video and Signal Based Surveillance, 25-28 August 2015, Karlsruhe, Germany.

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Abstract

Public buildings and large infrastructure are typically monitored by tens or hundreds of cameras, all capturing different physical spaces and observing different types of interactions and behaviours. However to date, in large part due to limited data availability, crowd monitoring and operational surveillance research has focused on single camera scenarios which are not representative of real-world applications. In this paper we present a new, publicly available database for large scale crowd surveillance. Footage from 12 cameras for a full work day covering the main floor of a busy university campus building, including an internal and external foyer, elevator foyers, and the main external approach are provided; alongside annotation for crowd counting (single or multi-camera) and pedestrian flow analysis for 10 and 6 sites respectively. We describe how this large dataset can be used to perform distributed monitoring of building utilisation, and demonstrate the potential of this dataset to understand and learn the relationship between different areas of a building.

Impact and interest:

1 citations in Scopus
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ID Code: 85118
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Crowd Counting, Pedestrian Flow Estimation, Intelligent Surveillance Systems, Database
DOI: 10.1109/AVSS.2015.7301796
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Pattern Recognition and Data Mining (080109)
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Funding:
Copyright Owner: Copyright 2015 [Please consult the author]
Deposited On: 06 Jul 2015 01:52
Last Modified: 12 Sep 2016 08:02

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