Computer vision for civil engineering applications

Summary

Computer vision for civil engineering applications

In recent years there has been a significant growth in the condition monitoring of civil engineering infrastructure using camera technologies. For example, depending upon the application, vehicle-borne cameras, UAV-borne cameras and space-borne cameras are rapidly replacing traditional manual inspection due to cost, reliability and safety advantages.

For each of these camera mounting options, there is also a wide range of camera types which can be used. For example, traditional cameras record RGB images to allow for the detection of the general appearance of their target. Alternatively, thermal cameras can also be used to determine heat, while hyperspectral images are used to detect different material types using spectral fingerprints.

Computer vision is the field of artificial intelligence used to derive information from these images and videos. It’s a powerful tool for processing image data recorded during the condition monitoring of civil engineering infrastructure. Therefore it is at the forefront of the AI revolution and thus a rapidly evolving field. In engineering it is commonly used for either inspection or monitoring:

Inspection: Damage detection, change detection, object detection, segmentation and structural component recognition of civil structures.

Monitoring: Measurement of displacements, stresses, strains, accelerations of civil structures, either under static or dynamic conditions.

Computer vision can be applied for a wide range of civil engineering applications, for example in structural engineering, geotechnical engineering, water engineering, construction engineering, transport engineering, environmental engineering, surveying, urban engineering and construction site safety.

If you have already secured, or will be able to secure scholarship funding for a PhD in computer vision in the above fields or a related field, please contact d.connolly@leeds.ac.uk to discuss next steps.

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