Transforming Physical Crime Scene into Geospatial-based Point Cloud Data

Authors

  • Rabi'atul'Adawiyah Azmil GI2RG, FBES, Universiti Teknologi Malaysia, Malaysia
  • Mohd Farid Mohd Ariff MSFG UTM-PDRM, FBES, Universiti Teknologi Malaysia, Malaysia
  • Ahmad Firdaus Razali GI2RG, FBES, Universiti Teknologi Malaysia, Malaysia
  • Suzanna Noor Azmy INSTEG, FBES, Universiti Teknologi Malaysia, Malaysia
  • Norhadija Darwin GI2RG, FBES, Universiti Teknologi Malaysia, Malaysia
  • Khairulnizam M. Idris GI2RG, FBES, Universiti Teknologi Malaysia, Malaysia
Volume: 14 | Issue: 3 | Pages: 13974-13981 | June 2024 | https://doi.org/10.48084/etasr.6888

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 reconstruction

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How to Cite

[1]
R. Azmil, M. F. Mohd Ariff, A. F. Razali, S. N. Azmy, N. Darwin, and K. M. Idris, “Transforming Physical Crime Scene into Geospatial-based Point Cloud Data”, Eng. Technol. Appl. Sci. Res., vol. 14, no. 3, pp. 13974–13981, Jun. 2024.

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