Automated semantic scene content extraction for Security, Safety, Construction and Maintenance
Lead Participant:
ARALIA SYSTEMS LIMITED
Abstract
The project brings existing Aralia IPR developed in response to applications in infrastructure, urban, transportation systems that benefit from the automated analysis of video images.
The project combines multispectral and 3D reconstruction of surfaces at high resolution, CNN based object detectors and scene context generation, supported by a semantic database that uses a lexicon appropriate to the rail industry problem space.
The objective of the project is to provide a low-cost, portable scene analysis system that addresses use-cases in surveillance, safety, construction, and asset management.
The project combines multispectral and 3D reconstruction of surfaces at high resolution, CNN based object detectors and scene context generation, supported by a semantic database that uses a lexicon appropriate to the rail industry problem space.
The objective of the project is to provide a low-cost, portable scene analysis system that addresses use-cases in surveillance, safety, construction, and asset management.
Lead Participant | Project Cost | Grant Offer |
---|---|---|
ARALIA SYSTEMS LIMITED | £36,410 | £ 22,909 |
People |
ORCID iD |
GLYNN WRIGHT (Project Manager) |