Sang-hun Sean Yu

This research demonstrates that structured photogrammetry and Virtual Reality (VR)-based forensic reconstructions significantly advance contemporary forensic practice. The study establishes a robust and forward-looking framework for forensic documentation, training, and analysis by integrating emerging digital technologies with traditional investigative methods. The Dundee Ground Truth (GT) Imaging Protocol is at the centre of this work, developed specifically to optimise the recording of complex and spatially constrained forensic scenes. The protocol enables high-precision capture and reconstruction using minimal photographic inputs, providing an efficient yet highly accurate approach to scene documentation.

As forensic methodologies continue to evolve, incorporating digital tools has become increasingly essential to meet the demands of modern investigative processes. Recent advancements in photogrammetry hardware—including high-resolution cameras, improved data storage, and enhanced computational power—have significantly increased data quality and processing efficiency. These technological improvements have expanded the relevance of photogrammetry far beyond forensic science, finding valuable applications in fields such as archaeology, environmental monitoring, architectural analysis, and cultural heritage preservation.

The adaptability of the GT protocol is further supported by the development of compact imaging systems and automated workflows, allowing for efficient deployment in hazardous, remote, or otherwise inaccessible locations. This streamlines data acquisition and reduces human error and the need for extensive on-site presence. By establishing a scalable and reliable system of documentation, the research reinforces the value of photogrammetry and VR in producing data-rich, navigable 3D models.

Ultimately, this research underscores the importance of interdisciplinary collaboration and ongoing innovation in advancing forensic science and digital spatial recording.

Names of Supervisors: 

• 1st - Prof. Chris Rowland
• 2nd- Prof Niamh Nic Daeid