2016-12-20T15:22:26 n920

Crowd counting database

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This dataset was collected for an assessment of a crowd counting alogorithm.

The dataset is a vision dataset taken from a QUT Campus and contains three challenging viewpoints, which are referred to as Camera A, Camera B and Camera C. The sequences contain reflections, shadows and difficult lighting fluctuations, which makes crowd counting difficult. Furthermore, Camera C is positioned at a particularly low camera angle, leading to stronger occlusion than is present in other datasets.

The QUT datasets are annotated at sparse intervals: every 100 frames for cameras B and C, and every 200 frames for camera A as this is a longer sequence. Testing is then performed by comparing the crowd size estimate to the ground truth at these sparse intervals, rather than at every frame. This closely resembles the intended real-world application of this technology, where an operator may periodically ‘query’ the system for a crowd count.

Due to the difficulty of the environmental conditions in these scenes, the first 400-500 frames of each sequence is set aside for learning the background model.

Access rights

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.

Geographical area of data collection



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

Image processing
Artifical intelligence and image processing
Crowd monitoring
Signal processing
Scene invariant
Computer vision
Local features
Information and computing sciences
Density estimation
Crowd counting

Cite this collection

QUT SAIVT: Speech, audio, image and video technologies research . (2012): Crowd counting database . [Queensland University of Technology]. http://dx.doi.org/10.4225/09/5858bfb708148


Creative Commons Attribution-Share Alike 4.0 (CC-BY-SA)


© Queensland University of Technology, 2012


Was collected by


Name: David Ryan


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Published - Open Access