Transforming Physical Crime Scene into Geospatial-based Point Cloud Data
Received: 11 January 2024 | Revised: 13 February 2024 and 10 March 2024 | Accepted: 11 March 2024 | Online: 1 June 2024
Corresponding author: Mohd Farid Mohd Ariff
Abstract
Terrestrial Laser Scanning (TLS) and Close-Range Photogrammetry (CRP) are advanced techniques for capturing 3D data in crime scene reconstruction, offering complementary information. Despite taking multiple scans and images from different angles to ensure a comprehensive model, limitations, such as device positioning, shadows, object distance, and laser beam angles prevent the creation of a complete crime scene model. Therefore, combining TLS and CRP data is crucial for achieving a comprehensive reconstruction. This study aims to transform a physical crime scene into a geospatial-based reconstructed model known as point clouds. The technique used was highly rich in realistic features, digitally reconstructed from TLS and CRP. The data sources were then fused via a rigid body transformation, creating a comprehensive crime scene model. The combined point cloud measurements were compared with measurements obtained from a high-precision Vernier caliper to ascertain their accuracy. The resulting Root Mean Square (RMSE) difference between the fused point cloud data and the high-precision caliper measurements was approximately ±4mm. The fusion of TLS and CRP data provides reliable and highly accurate 3D model point clouds, making it suitable for forensic applications.
Keywords:
laser scanning, photogrammetry, data fusion, point cloud, crime scene reconstructionDownloads
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Copyright (c) 2024 Rabi'atul'Adawiyah Azmil, Mohd Farid Mohd Ariff, Ahmad Firdaus Razali, Suzanna Noor Azmy, Norhadija Darwin, Khairulnizam M. Idris
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