City Photogrammetry & Auto Masking (Python)
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City Photogrammetry & Auto Masking (Python)

This study presents an automated approach to object masking in urban photogrammetry. Leveraging a pre-trained Mask R-CNN model within a Python framework, the methodology effectively removes transient objects such as vehicles and pedestrians, thereby enhancing feature matching and 3D reconstruction accuracy in complex urban environments.

Photogrammetry of the Heritage Centre and Roman Gate
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Photogrammetry of the Heritage Centre and Roman Gate

The underground passages of Exeter are a unique historical network beneath the city. This project focuses on scanning key surface connections, including the Heritage Centre and Roman Gate, to digitally integrate these subterranean spaces with the modern streetscape. Using photogrammetry, detailed 3D models are created to enhance spatial understanding and support historical research.