Journal of Environmental Biology

An investigation of environmental factors influencing quantitative accuracy and recognition rate of craniofacial reconstructions 

S. M. Kim¹, W. J. Lee², J. H. Cho³, C. M. Wilkinson⁴, C. U. Choi² and S. S. Lee¹* 

¹Medical Examiner?s Office, National Forensic Service, Wonju-26460, Republic of Korea

²Department of Forensic Medicine Investigation, National Forensic Service Seoul Institute, Seoul-08036, Republic of Korea

³Department of Orthodontics, School of Dentistry, Chonnam National University, Gwangju-61186, Republic of Korea

⁴Face Lab, Liverpool John Moores University, IC1 Liverpool Science Park, Liverpool-L3 5TF, United Kingdom

*Corresponding Author Email : sslee1418@gmail.com

Paper received: 04.06.2019??????? ?????????????????????????????????????? Revised received: 20.10.2019????????????? Accepted: 03.01.2020

Abstract

Aim: The accuracy of forensic craniofacial reconstruction/approximation can be influenced by a number of environmental factors. The aim of this study was to investigate how different average facial soft tissue depth datasets might influence the accuracy of craniofacial reconstruction employing two accuracy assessment methods;face-pool comparison and geometric surface comparison.

Methodology: Six craniofacial reconstructions were produced using three-dimensional modeling software from 3D skull images of live Korean adult subjects generated by cone-beam computerized tomography. The six craniofacial reconstructions were divided into two groups: three created using an outdated Korean averaged facial soft tissue thickness dataset, and three created using a recent one. The accuracies for six craniofacial reconstructions were measured using face-pool comparison and geometric surface comparison methods to estimate the influential level of average facial soft tissue depth datasets to craniofacial reconstructions.??????      

Results: In face-pool comparisons, the recent dataset demonstrated a higher recognition rate than the outdated one. The results were compared to those of geometric surface comparisons using the same six craniofacial reconstructions; a positive correlation was detected.      

Interpretation: The results suggest that appropriate averaged facial soft tissue depth datasets influence the accuracy of craniofacial reconstructions, and that the geometric surface comparison method might be interchangeable with face-pool comparison method to evaluate the accuracy of craniofacial reconstructions.  

Key words: Accuracy, Craniofacial reconstruction, Environmental factors, Geometric surface, Recognition rate

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