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On Crowd Density Estimation for Surveillance

On Crowd Density Estimation for Surveillance
On Crowd Density Estimation for Surveillance
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.
Rahmalan, Hidayah
e15bf66e-517d-4b63-b717-ea05c956d2e9
Nixon, Mark S.
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Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da
Rahmalan, Hidayah
e15bf66e-517d-4b63-b717-ea05c956d2e9
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carter, John N.
e05be2f9-991d-4476-bb50-ae91606389da

Rahmalan, Hidayah, Nixon, Mark S. and Carter, John N. (2006) On Crowd Density Estimation for Surveillance. International Conference on Crime Detection and Prevention, London, United Kingdom.

Record type: Conference or Workshop Item (Paper)

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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More information

Published date: 2006
Additional Information: Event Dates: June 2006
Venue - Dates: International Conference on Crime Detection and Prevention, London, United Kingdom, 2006-06-01
Organisations: Southampton Wireless Group

Identifiers

Local EPrints ID: 262852
URI: http://eprints.soton.ac.uk/id/eprint/262852
PURE UUID: d438e2e8-f0d4-48d9-8adf-2b4228172c79
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 18 Jul 2006
Last modified: 15 Mar 2024 02:35

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Contributors

Author: Hidayah Rahmalan
Author: Mark S. Nixon ORCID iD
Author: John N. Carter

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