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On crowd density estimation for surveillance
Abstract
The goal of this work is to use computer vision to measure crowd density in outdoor scenes. Crowd density estimation is an important task in crowd monitoring. The assessment is carried out using images of a graduation scene which illustrated variation of illumination due to textured brick surface, clothing and changes of weather. Image features were extracted using grey level dependency matrix, Minkowski fractal dimension and a new method called translation invariant orthonormal Chebyshev moments. The features were then classified into a range of density by using a self organizing map. Three different techniques were used and a comparison on the classification results investigates the best performance for measuring crowd density by vision.
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Citations
Cited by
Crowd Analysis Using Computer Vision Techniques
Silveira Jacques Junior, J., Musse, S., & Jung, C. (2010) · IEEE Signal Processing Magazine · doi:10.1109/msp.2010.937394 · Cited by 343
Crowd Counting Using Multiple Local Features
Ryan, D., Denman, S., Fookes, C., & Sridharan, S. (2009) · 2009 Digital Image Computing: Techniques and Applications · doi:10.1109/dicta.2009.22 · Cited by 309
Estimating Crowd Densities and Pedestrian Flows Using Wi-Fi and Bluetooth
Schauer, L., Werner, M., & Marcus, P. (2014) · Proceedings of the 11th International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services · doi:10.4108/icst.mobiquitous.2014.257870 · Cited by 180
Metadata
- Authors
- Rahmalan, H., Nixon, M. S., & Carter, J. N.
- Venue
- IET Conference on Crime and Security
- Publisher
- IEE
- Published
- 2006
- Volume
- 2006
- Pages
- 540-545
- OpenAlex
- W2049163084
- Cited by
- 170
- References
- 0
- FWCI
- 6.79
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: On crowd density estimation for surveillance. https://app.cochat.ai/papers/10.1049/ic:20060360
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- Rahmalan, H., Nixon, M. S., & Carter, J. N. (2006). On crowd density estimation for surveillance. IET Conference on Crime and Security. https://doi.org/10.1049/ic%3A20060360
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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