Related Experiment Video
Updated: Mar 19, 2026
Quantitative Assessment Protocol for Facial Soft Tissue Volumetric Changes with Stereophotogrammetry
Published on: December 9, 2025
Digital Forensic Facial Reconstruction using Population Specific Soft Tissue Thickness Data: A Comparative Study of
Arjun Kundu1, Astha Pandey2, Dharmesh Silajiya3
1PhD Research Scholar, School of Doctoral Studies and Research, National Forensic Sciences University, Gandhinagar, Gujarat, India.
Aim:
Present study evaluates the impact of different regional FSTT datasets on the accuracy of computerized forensic facial reconstructions in a contemporary Indian context.
Material And Method:
A 40-year-old Indian man's CT image was converted into a 3D skull model in InVesalius 3.1. Geomagic Freeform Plus (2022.1.31) and Touch X hardware sculpted facial reconstructions. Use FSTT values from Gujarati, North Indian, and South Indian datasets to place landmark-specific soft tissue markers. RMS error and color-coded deviation maps were calculated by comparing each generated face to the subject's facial surface to assess reconstruction accuracy.
Result:
Quantitative research showed the South Indian model has the lowest RMS error (3.351 mm), followed by North Indian (3.754 mm) and Gujarati (4.376 mm). This suggests population matching increases geometric integrity. The population-matched model had less error for the highest orbital and cheek deviations in qualitative assessments with consistent error patterns.
Conclusion:
Population-specific soft-tissue reference data significantly enhance the anatomical accuracy of forensic facial reconstruction. Comprehensive regional FSTT databases and advanced digital modeling are recommended for reliable human identification. Persistent data gaps and anatomical variability highlight the need for ongoing research.
