The use of 3D modelling and the evolving digital virtual/mixed reality methodologies in gun-related homicides

Abstract

Currently, forensic science is experiencing a major transformation. The shift from traditional manual documentation such as sketches and 2D photography, to high-tech 3D reconstructions, aims to capture crime scenes and examine human remains in detailed digital forms. This dissertation titled “The Use of 3D Modelling and the Evolving Digital Virtual/Mixed Reality Methodologies in Gun-Related Homicides” explores how these technologies enhance forensic reconstructions, examines their legal implications and practical applications. Furthermore, this study compares ground-level practical perspectives against academic theory to determine the most effective investigative workflows. For this reason, qualitative methodology has been chosen based on semi-structured interviews, with a purposive sample of four experts. This research also proposes a five-phase workflow using tools such as 3D laser scanning, photogrammetry and 3D MSCT, among other technologies. This is aimed at integrating initial scene capture, the Virtopsy approach for internal documentation, data fusion, meticulous analysis and legal presentation. A key finding during this study is that compared to traditional reports, immersive Virtual Reality (VR) and Mixed Reality (MR) environments that are created by using software like Unity 3D, help laypersons ‘live the scene’, therefore improving their understanding of complex spatial dynamics and bullet trajectories. This study also emphasises that 3D reconstructions ensure objectivity and the permanent preservation of evidence, especially with regards to cold cases. This research also acknowledges the fact that bridging the trust gap in the legal system requires strict Standard Operating Procedures (SOPs). Also, to maintain scientific validity and at the same time counter scepticism, providing raw data and audit trails is paramount. Ultimately, future directions in 3D technologies point toward a shared vision of increased automation through AI assisted analysis and robotic data capture, so that scene contamination would ideally be minimised and complex manual rendering processes would be significantly reduced.