2017-01-23T14:49:21 n1251

SAIVT-QUT Crowd Counting

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SAIVT-QUT Crowd Counting Database

Overview

This database contains three sequences annotated for crowd counting, captured on a university campus. Sequences are sparsely annotated (every 100 or 200 frames) over the approximately 5,000 or 10,000 frame sequence duration. Annotation is local, in that the location of each individual person in the frames is provided. Annotation is also provided for the PETS 2006 and 2009 datasets (although please note that you will need to download these databases separately). Contact Dr Simon Denman for more information.

Licensing

The SAIVT-QUT Crowd Counting database is © 2012 QUT and is licensed under the Creative Commons Attribution-ShareAlike 3.0 Australia License.

Attribution

To attribute this database, please include the following citation: Ryan, David, Denman, Simon, Sridharan, Sridha, & Fookes, Clinton B. (2012) Scene invariant crowd counting and crowd occupancy analysis. In Video Analytics for Business Intelligence [Studies in Computational Intelligence, Volume 409]. Springer-Verlag, Germany, pp. 161-198. See the full paper on eprints.

Acknowleding the database in your publications

In addition to citing our paper, we kindly request that the following text be included in an acknowledgements section at the end of your publications: We would like to thank the SAIVT Research Labs at Queensland University of Technology (QUT) for freely supplying us with the SAIVT-QUT Crowd Counting database for our research. If you use the annotation data for either the PETS2006 or PETS2009 databases, you should also cite/acknowledge these databases in the appropriate method as outlined by the database creators, in addition to citing and acknowledging this database as outlined above and in the LICENCE.txt file.

Installing the database

Acknowledging the Database in your Publications Installing the SAIVT-QUT Crowd Counting database Download and unzip the following archive: SAIVT_QUTCrowdCountingDatabase.tar.gz (933 MB). Upon downloading and unzipping the database, you should have the following directory structure:

SAIVT-QUTCrowdCountingDatabase 
+--Datasets 
+--PETS2006 
+--PETS2009 
+--QUT 
+--Results 
+--PETS2006 
+--PETS2009 
+--QUT 
+-- LICENSE.txt 
+-- README.txt 
+-- Ryan2011 - Scene invariant crowd counting.pdf 

+-- Ryan2012 - Scene invariant crowd counting and crowd occupancy analysis.pdf

The database is located in the 'Datasets/QUT' subdirectory. Calibration and ground truth annotation is included within this directory, as well as a clean background image and region of interest for each of the three sequences. Ground truth annotation for the PETS2006 and PETS2009 databases are contained within the 'Datasets/PETS2006' and 'Datasets/PETS2009' subdirectories. A summary of this follows:

 

Video

Calibration

ROI

Ground Truth 
('dot' annotations)

Initial Background 
Frame

PETS 2009 
View 1

No (1)

Yes

Yes

Yes

Yes

PETS 2009 
View 2

No (1)

Yes

Yes

Yes

Yes

PETS 2006 
View 3

No (2)

Yes

Yes

Yes

No (3)

PETS 2006 
View 4

No (2)

Yes

Yes

Yes

No (3)

Camera A 
QUT

Yes

Yes

Yes

Yes

Yes

Camera B 
QUT

Yes

Yes

Yes

Yes

Yes

Camera C 
QUT

Yes

Yes

Yes

Yes

Yes

Access rights

This data is freely available for download. Contact Dr Simon Denman for more information. In addition to citing our paper, we kindly request that the following text be included in an acknowledgements section at the end of your publications: We would like to thank the SAIVT Research Labs at Queensland University of Technology (QUT) for freely supplying us with the SAIVT-QUT Crowd Counting database for our research. If you use the annotation data for either the PETS2006 or PETS2009 databases, you should also cite/acknowledge these databases in the appropriate method as outlined by the database creators, in addition to citing and acknowledging this database as outlined above and in the LICENCE.txt file.

Geographical area of data collection

text
Z Block Level 4 Foyer, QUT Gardens Point Campus

Publications

Ryan, David, Denman, Simon, Sridharan, Sridha, & Fookes, Clinton B. (2012) Scene invariant crowd counting and crowd occupancy analysis. In Video Analytics for Business Intelligence [Studies in Computational Intelligence, Volume 409]. Springer-Verlag, Germany, pp. 161-198. http://dx.doi.org/10.1007/978-3-642-28598-1_6

Research areas

Crowd Counting

Cite this collection

QUT SAIVT: Speech, audio, image and video technologies research . (2016): SAIVT-QUT Crowd Counting. [Queensland University of Technology]. https://doi.org/10.4225/09/58858af7585ad

Licence

Creative Commons Attribution-Share Alike 3.0 (CC-BY-SA)

Copyright

© Queensland University of Technology, 2012

Connections

Contacts

Name: Dr Simon Denman
Phone: +61731389329

Other

Date record created:
2016-06-30T15:05:01
Date record modified:
2017-01-23T14:49:21
Record status:
Published - Open Access