A computerized facial approximation method for archaic humans based on dense facial soft tissue thickness depths

Abstract

Facial approximation (FA) is a common tool used to recreate the possible facial appearance of a deceased person based on the relationship between soft tissue and the skull. Although this technique has been primarily applied to modern humans in the realm of forensic science and archaeology, only a few studies have attempted to produce FAs for archaic humans. This study presented a computerized FA approach for archaic humans based on the assumption that the facial soft tissue thickness depths (FSTDs) of modern living humans are similar to those of archaic humans. Additionally, we employed geometric morphometrics (GM) to examine the geometric morphological variations between the approximated faces and modern human faces. Our method has been applied to the Jinniushan (JNS) 1 archaic human, which is one of the most important fossils of the Middle Pleistocene, dating back to approximately 260,000 BP. The overall shape of the approximated face has a relatively lower forehead and robust eyebrows; a protruding, wider, and elongated middle and upper face; and a broad and short nose. Results also indicate skull morphology and the distribution of FSTDs influence the approximated face. These experiments demonstrate that the proposed method can approximate a plausible and reproducible face of an archaic human.

Age- and Sex-Related Measurements of Total Craniofacial Soft Tissue Thickness and Fat in a Central Chinese Population

“…This process needs to first determine the craniofacial classification database according to the age, gender, ethnicity, and other information of the skull to be restored; then, this process uses the average soft tissue thickness of the skull feature points in the classification database as the soft tissue thickness of the skull feature points to be restored. 13 Therefore, the richer the soft tissue thickness data in the craniofacial classification database, the more accurate the restored face of the ancients. In this study, the soft tissue thickness data of 41 craniofacial features were obtained from 280 CT samples of the head and face of central Chinese people, supplementing the Chinese craniofacial classification database.…”

“…(1) measuring in the normal direction along the facial landmarks or skull landmarks, (2) measuring in the straight direction along the facial features or skull feature points, and (3) determining the corresponding craniofacial landmarks according to the anatomical relationship and then using their connection as the measurement direction. 13 Due to the complex geometry of the head and presence of noise in the skull modeling process, the normal direction of the same position of different skulls is not necessarily the same; thus, the soft tissue in this article was measured along a straight line. 36 The measurement direction and CFSTT are shown in Figure 3.…”

“…determining the corresponding craniofacial landmarks according to the anatomical relationship and then using their connection as the measurement direction 13 …”

“…In addition, the facial soft tissue thickness data of South Korean, 5 Brazilian, 6 White, 7 Black, 8 Indonesian, 9 French, 10 Japanese, 11 and South African 12 individuals have been collected and analyzed. In China, Shui et al 13 measured the facial soft tissue thickness of individuals in Northern China and used these data to study facial restoration; Chen, 14 Dong, 15 Chung 16 and Deng et al 17 measured facial soft tissue and analyzed data from different regions of China. However, data of the CFSTT of individuals in central China are still lacking.…”

A Comparison of Semilandmarking Approaches in the Analysis of Size and Shape

“…We used a hybrid non-rigid registration approach [ 39 ] to deform the template specimen to fit each target specimen and then projected the semilandmarks from the warped template onto each specimen by searching for the nearest points on its surface, to yield semilandmarks across all specimens. Unlike rigid registration, in fitting, each vertex of the template can be moved freely with stretching based on a non-rigid transformation and landmarks acting as constraints.…”