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Correlation Between Average Tissue Depth Data and Quantitative Accuracy of Forensic Craniofacial Reconstructions Measured by Geometric Surface Comparison Method
Author(s) -
Lee WonJoon,
Wilkinson Caroline M.,
Hwang HyeonShik,
Lee SangMi
Publication year - 2015
Publication title -
journal of forensic sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.715
H-Index - 96
eISSN - 1556-4029
pISSN - 0022-1198
DOI - 10.1111/1556-4029.12726
Subject(s) - face (sociological concept) , artificial intelligence , computer science , software , craniofacial , reliability (semiconductor) , pattern recognition (psychology) , hard tissue , statistics , computer vision , mathematics , medicine , dentistry , psychiatry , social science , power (physics) , physics , quantum mechanics , sociology , programming language
Accuracy is the most important factor supporting the reliability of forensic facial reconstruction ( FFR ) comparing to the corresponding actual face. A number of methods have been employed to evaluate objective accuracy of FFR . Recently, it has been attempted that the degree of resemblance between computer‐generated FFR and actual face is measured by geometric surface comparison method. In this study, three FFR s were produced employing live adult Korean subjects and three‐dimensional computerized modeling software. The deviations of the facial surfaces between the FFR and the head scan CT of the corresponding subject were analyzed in reverse modeling software. The results were compared with those from a previous study which applied the same methodology as this study except average facial soft tissue depth dataset. Three FFR s of this study that applied updated dataset demonstrated lesser deviation errors between the facial surfaces of the FFR and corresponding subject than those from the previous study. The results proposed that appropriate average tissue depth data are important to increase quantitative accuracy of FFR .