A Comparative Assessment of Virtual Reconstruction Methods for Indoor Crime Scenes​

When generating virtual reconstructions of crime scenes for use as either investigative or training tools, the accuracy of the spatial data underpinning these reconstructions must be fully understood. Through recording indoor crime scenes using virtualization technologies, this research aims to assess the thoroughness of the spatial data collected at the scene, whilst also considering the potential impact of each recording method on the site. A simulated fire scene set up in a domestic dwelling in the Guldborgsund municipality, Denmark, was selected as a case study. First, a multi-modal dataset of point clouds was assembled using a (1) Leica RTC360 terrestrial laser system (TLS), a (2) Leica BLK2GO handheld mobile laser scanner (HMLS), (3) Matterport Pro2 3D Camera structured-light scanner (SL) and (4) Canon EOS 5D Mark III (DSLR).
Owing to its nominal precision and resolution, we identified the point cloud obtained using the TLS device as the baseline reference system for the comparative analysis of the selected image capture methods.
We evaluated the chosen imaging approaches against the potential impacts on the scene during image capture. The present analysis included the assessment of the accuracy and quality of point clouds through comparison with the baseline reference data using visual inspection, inter-cloud distance estimation and feature measurement. Due to the different nature of the methods, it is not our intention to identify the overarching best recording method, conversely, we are interested in benchmarking the performances of the selected capture methods both qualitatively and quantitively in the context of the incident.