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Improving Facial Reproduction Using Empirical Modeling, Final Technical Report

NCJ Number
Date Published
May 2010
105 pages

This study developed a new technique for estimating the facial soft tissue thickness at the 21 traditional craniometrical landmarks used in forensic facial reconstruction for the purpose of identifying deceased persons from skeletal remains.


Currently, the soft tissue thicknesses or marker lengths used in forensic facial reconstruction are the average tissue depths of various examined cadavers of different ethnicity, sex, and body type. The new technique proposed in this report uses a nonparametric modeling technique to predict the facial tissue depths based on a unique skull input. This modeling technique was tested on three male skulls from the William Bass Donated Collection at the University of Tennessee. A certified forensic artist constructed the facial reconstructions. The facial reconstructions using tabled tissue thicknesses were compared to the reconstructions of the same subject using the inferential models' predicted tissue thicknesses. Although certain landmarks, particularly the zygomatics, were estimated too large, overall the model seemed to do a better job of estimating the face in each case. The development of the methodology for this pilot study has been completed. The 100 live male subjects' computed tomography (CT) images have been identified. CT images of 100 Caucasian male subjects' skulls were used to build a database of facial tissue thicknesses and input predictors for the nonparametric model. The inputs to the model are various cranial bone thicknesses and measurements along specific anatomical lines. These are used to predict the facial tissue thicknesses at the traditional landmarks using a Nonparametric Kernel Regression model. The tissue and bone measurements were performed with the software package IDAS. Hetero-Associative Kernel Regression and Inferential Kernel Regression models were built using the measurements from the 100 male subjects. The methodology and results of the models' performance testing are described. 8 tables, 35 figures, 19 references, and appended supplementary information

Date Published: May 1, 2010