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Automated image understanding for long term wide-area surveillance of dynamic scene objects.


Durham Computer Science research on computer vision algorithms enables automated image understanding to provide long term wide-area surveillance of dynamic scene objects (e.g. people, vehicles) addressing questions such as: “Is there anything there?” (detection); “What is it?” (classification); “Where is it?” (localization); and “What is it’s behaviour?” (tracking).

This research, as part the SAPIENT programme, informs scientific work by the governments of UK, USA, Canada, Australia, New Zealand and Netherlands on wide-area, multi-sensor surveillance systems. Our research has contributed to £23.2 million investment in multi-sensor surveillance systems (UK/US government/industry), £11.3 million of additional commercial income to UK companies and supported the creation of around 55 additional science and engineering jobs across six organisations.

As of 2022, the open software architecture developed within the SAPIENT programme is now being used by NATO for the evaluation of counter-drone technologies.

UK government paper (guidance): SAPIENT autonomous sensor system

Press release: NATO trials Dstl standard for counter-drone systems - DSTL news story

Press release: Swarming drones concept flies closer to reality - DSTL press release

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