Connie L. Parks

Preliminary assessment of facial soft tissue thickness utilizing three-dimensional computed tomography models of living individuals

Facial approximation is the technique of developing a representation of the face from the skull of an unknown individual. Facial approximation relies heavily on average craniofacial soft tissue depths. For more than a century, researchers have employed a broad array of tissue depth collection methodologies, a practice which has resulted in a lack of standardization in craniofacial soft tissue depth research. To combat such methodological inconsistencies, Stephan and Simpson 2008 [15] examined and synthesized a large number of previously published soft tissue depth studies. Their comprehensive meta-analysis produced a pooled dataset of averaged tissue depths and a simplified methodology, which the researchers suggest be utilized as a minimum standard protocol for future craniofacial soft tissue depth research. The authors of the present paper collected craniofacial soft tissue depths using three-dimensional models generated from computed tomography scans of living males and females of four self-identified ancestry groups from the United States ranging in age from 18 to 62 years. This paper assesses the differences between: (i) the pooled mean tissue depth values from the sample utilized in this paper and those published by Stephan 2012 [21] and (ii) the mean tissue depth values of two demographically similar subsets of the sample utilized in this paper and those published by Rhine and Moore 1984 [16]. Statistical test results indicate that the tissue depths collected from the sample evaluated in this paper are significantly and consistently larger than those published by Stephan 2012 [21]. Although a lack of published variance data by Rhine and Moore 1984 [16] precluded a direct statistical assessment, a substantive difference was also concluded. Further, the dataset presented in this study is representative of modern American adults and is, therefore, appropriate for use in constructing contemporary facial approximations.

Accuracy of standard craniometric measurements using multiple data formats

UNLABELLED With continuing advancements in biomedical imaging technologies, anthropologists are increasingly making use of data derived from indirect measurement and analysis of skeletal material. To that end, the purpose of this study was to test the reliability of 26 standard craniometric measurements routinely utilized in forensic casework across several different imaging technologies. Measurements from five crania of known individuals were collected in duplicate by two anthropologists via computed tomography (CT) scans and three-dimensional (3D) laser scans of the known skulls. The laser scans were also used to create prototype models of the known skulls. These prototypes were, themselves, laser-scanned, and measurements were also collected from the prototypes and the laser scans of the prototypes. Measurement sets from each technology were then compared with one another using the previously collected osteometric measurements taken on the crania themselves as the ground truth. RESULT indicate that, while the majority of measurements showed no significant differences across data formats, a handful were found to be problematic for particular technologies. For instance, measurements taken in a supero-inferior direction (e.g., BBH, OBH) from CT scans were prone to greater deviation from direct measurements of the cranium than other technologies, especially for CT scans taken at 5 mm thickness and increment. Also, several measurements defined by Type 1 landmarks, particularly those occurring at complicated or indistinct suture junctures (e.g., ASB, ZMB), were found to have high variance across all technologies while measurements based on Type 3 landmarks proved to be highly reproducible. This is contrary to measurements taken directly on crania, in which measures defined by Type 1 landmarks are typically the most reliable, likely attributable to diminished or totally obscured suture definition in the scan data. If medical imaging data are to be increasingly utilized in anthropological studies, it may be prudent to bear in mind that the reliability of measurements taken on an actual skull may not be the same as for measurements taken from medical scans.

Preliminary performance assessment of computer automated facial approximations using computed tomography scans of living individuals

ReFace (Reality Enhancement Facial Approximation by Computational Estimation) is a computer-automated facial approximation application jointly developed by the Federal Bureau of Investigation and GE Global Research. The application derives a statistically based approximation of a face from a unidentified skull using a dataset of ~400 human head computer tomography (CT) scans of living adult American individuals from four ancestry groups: African, Asian, European and Hispanic (self-identified). To date only one unpublished subjective recognition study has been conducted using ReFace approximations. It indicated that approximations produced by ReFace were recognized above chance rates (10%). This preliminary study assesses: (i) the recognizability of five ReFace approximations; (ii) the recognizability of CT-derived skin surface replicas of the same individuals whose skulls were used to create the ReFace approximations; and (iii) the relationship between recognition performance and resemblance ratings of target individuals. All five skin surface replicas were recognized at rates statistically significant above chance (22-50%). Four of five ReFace approximations were recognized above chance (5-18%), although with statistical significance only at the higher rate. Such results suggest reconsideration of the usefulness of the type of output format utilized in this study, particularly in regard to facial approximations employed as a means of identifying unknown individuals.

Assessment of presentation methods for ReFace computerized facial approximations.

Facial approximations (whether clay sculptures, sketches, or computer-generated) can be presented to the public in a variety of layouts, but there are currently no clear indicators as to what style of presentation is most effective at eliciting recognition. The primary purpose of this study is to determine which of five presentation methods produces the most favorable recognition results. A secondary goal of the research is to evaluate a new method for assessing the accuracy of facial approximations. Previous studies have evaluated facial approximation effectiveness using standards similar to studies of eyewitness identification in which a single, definitive choice must be made by the research participant. These criteria seem inappropriate given that facial approximation is strictly an investigative tool to help narrow the search for potential matching candidates in the process of identification. Results from the study showed a higher performance for methods utilizing more than one image of the approximation, but which specific method performed best varied among approximation subjects. Also, results for all five presentation methods showed that, when given the opportunity to select more than one approximation, participants were consistently better at identifying the correct approximation as one of a few possible matches to the missing person than they were at singling out the correct approximation. This suggests that facial approximations have perhaps been undervalued as investigative tools in previous research.

Automated facial recognition of manually generated clay facial approximations: Potential application in unidentified persons data repositories

This research examined how accurately 2D images (i.e., photographs) of 3D clay facial approximations were matched to corresponding photographs of the approximated individuals using an objective automated facial recognition system. Irrespective of search filter (i.e., blind, sex, or ancestry) or rank class (R1, R10, R25, and R50) employed, few operationally informative results were observed. In only a single instance of 48 potential match opportunities was a clay approximation matched to a corresponding life photograph within the top 50 images (R50) of a candidate list, even with relatively small gallery sizes created from the application of search filters (e.g., sex or ancestry search restrictions). Increasing the candidate lists to include the top 100 images (R100) resulted in only two additional instances of correct match. Although other untested variables (e.g., approximation method, 2D photographic process, and practitioner skill level) may have impacted the observed results, this study suggests that 2D images of manually generated clay approximations are not readily matched to life photos by automated facial recognition systems. Further investigation is necessary in order to identify the underlying cause(s), if any, of the poor recognition results observed in this study (e.g., potential inferior facial feature detection and extraction). Additional inquiry exploring prospective remedial measures (e.g., stronger feature differentiation) is also warranted, particularly given the prominent use of clay approximations in unidentified persons casework.