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Yang X, Li R, Yang X, Zhou Y, Liu Y, Han JDJ. Coordinate-wise monotonic transformations enable privacy-preserving age estimation with 3D face point cloud. SCIENCE CHINA. LIFE SCIENCES 2024; 67:1489-1501. [PMID: 38573362 DOI: 10.1007/s11427-023-2518-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/26/2023] [Accepted: 12/25/2023] [Indexed: 04/05/2024]
Abstract
The human face is a valuable biomarker of aging, but the collection and use of its image raise significant privacy concerns. Here we present an approach for facial data masking that preserves age-related features using coordinate-wise monotonic transformations. We first develop a deep learning model that estimates age directly from non-registered face point clouds with high accuracy and generalizability. We show that the model learns a highly indistinguishable mapping using faces treated with coordinate-wise monotonic transformations, indicating that the relative positioning of facial information is a low-level biomarker of facial aging. Through visual perception tests and computational 3D face verification experiments, we demonstrate that transformed faces are significantly more difficult to perceive for human but not for machines, except when only the face shape information is accessible. Our study leads to a facial data protection guideline that has the potential to broaden public access to face datasets with minimized privacy risks.
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Affiliation(s)
- Xinyu Yang
- School of Life Sciences, Peking University, Beijing, 100871, China
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Runhan Li
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China
| | - Xindi Yang
- Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China
| | - Yong Zhou
- Clinical Research Institute, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yi Liu
- Beijing Key Lab of Traffic Data Analysis and Mining, School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China
| | - Jing-Dong J Han
- Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Center for Quantitative Biology (CQB), Peking University, Beijing, 100871, China.
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Matthews HS, Mahdi S, Penington AJ, Marazita ML, Shaffer JR, Walsh S, Shriver MD, Claes P, Weinberg SM. Using data-driven phenotyping to investigate the impact of sex on 3D human facial surface morphology. J Anat 2023. [PMID: 36943032 DOI: 10.1111/joa.13866] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Revised: 02/28/2023] [Accepted: 03/06/2023] [Indexed: 03/23/2023] Open
Abstract
The effects of sex on human facial morphology have been widely documented. Because sexual dimorphism is relevant to a variety of scientific and applied disciplines, it is imperative to have a complete and accurate account of how and where male and female faces differ. We apply a comprehensive facial phenotyping strategy to a large set of existing 3D facial surface images. We investigate facial sexual dimorphism in terms of size, shape, and shape variance. We also assess the ability to correctly assign sex based on shape, both for the whole face and for subregions. We applied a predefined data-driven segmentation to partition the 3D facial surfaces of 2446 adults into 63 hierarchically linked regions, ranging from global (whole face) to highly localized subparts. Each facial region was then analyzed with spatially dense geometric morphometrics. To describe the major modes of shape variation, principal components analysis was applied to the Procrustes aligned 3D points comprising each of the 63 facial regions. Both nonparametric and permutation-based statistics were then used to quantify the facial size and shape differences and visualizations were generated. Males were significantly larger than females for all 63 facial regions. Statistically significant sex differences in shape were also seen in all regions and the effects tended to be more pronounced for the upper lip and forehead, with more subtle changes emerging as the facial regions became more granular. Males also showed greater levels of shape variance, with the largest effect observed for the central forehead. Classification accuracy was highest for the full face (97%), while most facial regions showed an accuracy of 75% or greater. In summary, sex differences in both size and shape were present across every part of the face. By breaking the face into subparts, some shape differences emerged that were not apparent when analyzing the face as a whole. The increase in facial shape variance suggests possible evolutionary origins and may offer insights for understanding congenital facial malformations. Our classification results indicate that a high degree of accuracy is possible with only parts of the face, which may have implications for biometrics applications.
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Affiliation(s)
- Harold S Matthews
- Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Soha Mahdi
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
| | - Anthony J Penington
- Facial Sciences Research Group, Murdoch Children's Research Institute, Parkville, 3052, Australia
- Department of Plastic and Maxillofacial Surgery, Royal Children's Hospital, Melbourne, 3052, Australia
- Department of Pediatrics, University of Melbourne, Melbourne, 3052, Australia
| | - Mary L Marazita
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
| | - Susan Walsh
- Department of Biology, Indiana University Purdue University Indianapolis, Indianapolis, Indiana, 46202, USA
| | - Mark D Shriver
- Department of Anthropology, Pennsylvania State University, State College, Pennsylvania, 16802, USA
| | - Peter Claes
- Department of Human Genetics, KU Leuven, 3000, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Herestraat 49, 3000, Leuven, Belgium
- Facial Sciences Research Group, Murdoch Children's Research Institute, Parkville, 3052, Australia
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, 3000, Leuven, Belgium
| | - Seth M Weinberg
- Center for Craniofacial and Dental Genetics, Department of Oral and Craniofacial Sciences, University of Pittsburgh, Pittsburgh, Pennsylvania, 15219, USA
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, Pennsylvania, 15261, USA
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Local transform directional pattern and optimization driven DBN for age estimation. EVOLUTIONARY INTELLIGENCE 2022. [DOI: 10.1007/s12065-020-00363-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Richmond S, Zhurov AI, Ali ABM, Pirttiniemi P, Heikkinen T, Harila V, Silinevica S, Jakobsone G, Urtane I. Exploring the midline soft tissue surface changes from 12 to 15 years of age in three distinct country population cohorts. Eur J Orthod 2021; 42:517-524. [PMID: 31748803 DOI: 10.1093/ejo/cjz080] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
INTRODUCTION Several studies have highlighted differences in the facial features in a White European population. Genetics appear to have a major influence on normal facial variation, and environmental factors are likely to have minor influences on face shape directly or through epigenetic mechanisms. AIM The aim of this longitudinal cohort study is to determine the rate of change in midline facial landmarks in three distinct homogenous population groups (Finnish, Latvian, and Welsh) from 12.8 to 15.3 years of age. This age range covers the pubertal growth period for the majority of boys and girls. METHODS A cohort of children aged 12 were monitored for facial growth in three countries [Finland (n = 60), Latvia (n = 107), and Wales (n = 96)]. Three-dimensional facial surface images were acquired (using either laser or photogrammetric methods) at regular intervals (6-12 months) for 4 years. Ethical approval was granted in each country. Nine midline landmarks were identified and the relative spatial positions of these surface landmarks were measured relative to the mid-endocanthion (men) over a 4-year period. RESULTS This study reports the children who attended 95 per cent of all scanning sessions (Finland 48 out of 60; Latvia 104 out of 107; Wales 50 out of 96). Considerable facial variation is seen for all countries and sexes. There are clear patterns of growth that show different magnitudes at different age groups for the different country groups, sexes, and facial parameters. The greatest single yearly growth rate (5.4 mm) was seen for Welsh males for men-pogonion distance at 13.6 years of age. Males exhibit greater rates of growth compared to females. These variations in magnitude and timings are likely to be influenced by genetic ancestry as a result of population migration. CONCLUSION The midline points are a simple and valid method to assess the relative spatial positions of facial surface landmarks. This study confirms previous reports on the subtle differences in facial shapes and sizes of male and female children in different populations and also highlights the magnitudes and timings of growth for various midline landmark distances to the men point.
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Affiliation(s)
- Stephen Richmond
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Alexei I Zhurov
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Azrul Bin Mohd Ali
- Orthodontic Department, Applied Clinical Research and Public Health, School of Dentistry, College of Biomedical and Life Sciences, Heath Park, Cardiff, UK
| | - Pertti Pirttiniemi
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Tuomo Heikkinen
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Virpi Harila
- Oral Development and Orthodontics, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Signe Silinevica
- Orthodontic Department, RSU Institute of Stomatology, Rīga, Latvia
| | | | - Ilga Urtane
- Orthodontic Department, RSU Institute of Stomatology, Rīga, Latvia
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Jandová M, Daňko M, Urbanová P. Age verification using random forests on facial 3D landmarks. Forensic Sci Int 2020; 318:110612. [PMID: 33285472 DOI: 10.1016/j.forsciint.2020.110612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 11/16/2020] [Accepted: 11/19/2020] [Indexed: 01/09/2023]
Abstract
Three-dimensional facial images are becoming more and more widespread. As such images provide more information about facial morphology than 2D imagery, they show great promise for use in future forensic applications, including age estimation and verification. This paper proposes an approach using random forests, a machine learning method, to develop and test models for classification of legal age thresholds (15 years and 18 years) using 3D facial landmarks. Our approach was developed on a set of 3D facial scans from 394 Czech individuals (194 males and 200 females) aged between 10 and 25 years. The dataset was retrieved from a sizable database of Central European faces - The FIDENTIS 3D Face Database. Three main types of input variables were processed using random forests: I) shape (size-invariant) coordinates of 3D landmarks, II) size and shape coordinates of 3D landmarks, and III) inter-landmark distances, angles and indices. The performance rates for the combinations of variables and age threshold were expressed in terms of sensitivity and specificity. The overall accuracy rates varied from 71.4%-91.5% (when the male and female samples were pooled). In general, higher accuracy was achieved for the age limit of 18 years than for 15 years. Whereas size-variant variables showed a better performance rate for the age limit of 15 years, the size-invariant variables (i.e., shape variables) were better for classifying individuals under 18 years. The verification models grounded on traditional variables (distances, angles, indices) yielded consistently higher performance rates on females than on males, whereas the inverse trend was observed for the models built on 3D coordinates. The results indicate that age verification based on 3D facial data with processing by the random forests method has high potential for further forensic or biometric applications.
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Affiliation(s)
- Marie Jandová
- Laboratory of Morphology and Forensic Anthropology, Department of Anthropology, Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic.
| | - Marek Daňko
- Laboratory of Morphology and Forensic Anthropology, Department of Anthropology, Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic.
| | - Petra Urbanová
- Laboratory of Morphology and Forensic Anthropology, Department of Anthropology, Faculty of Science, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Republic.
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Pressler MP, Geisler EL, Hallac RR, Seaward JR, Kane AA. The Use of Eye Tracking to Discern the Threshold at Which Metopic Orbitofrontal Deformity Attracts Attention. Cleft Palate Craniofac J 2020; 57:1392-1401. [PMID: 32489115 DOI: 10.1177/1055665620926014] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
INTRODUCTION AND OBJECTIVES Surgical treatment for trigonocephaly aims to eliminate a stigmatizing deformity, yet the severity that captures unwanted attention is unknown. Surgeons intervene at different points of severity, eliciting controversy. This study used eye tracking to investigate when deformity is perceived. MATERIAL AND METHODS Three-dimensional photogrammetric images of a normal child and a child with trigonocephaly were mathematically deformed, in 10% increments, to create a spectrum of 11 images. These images were shown to participants using an eye tracker. Participants' gaze patterns were analyzed, and participants were asked if each image looked "normal" or "abnormal." RESULTS Sixty-six graduate students were recruited. Average dwell time toward pathologic areas of interest (AOIs) increased proportionally, from 0.77 ± 0.33 seconds at 0% deformity to 1.08 ± 0.75 seconds at 100% deformity (P < .0001). A majority of participants did not agree an image looked "abnormal" until 90% deformity from any angle. CONCLUSION Eye tracking can be used as a proxy for attention threshold toward orbitofrontal deformity. The amount of attention toward orbitofrontal AOIs increased proportionally with severity. Participants did not generally agree there was "abnormality" until deformity was severe. This study supports the assertion that surgical intervention may be best reserved for more severe deformity.
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Affiliation(s)
- Mark P Pressler
- Department of Plastic Surgery, 12334UT Southwestern, Dallas, TX, USA.,Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA
| | - Emily L Geisler
- Department of Plastic Surgery, 12334UT Southwestern, Dallas, TX, USA.,Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA
| | - Rami R Hallac
- Department of Plastic Surgery, 12334UT Southwestern, Dallas, TX, USA.,Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA
| | - James R Seaward
- Department of Plastic Surgery, 12334UT Southwestern, Dallas, TX, USA.,Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA
| | - Alex A Kane
- Department of Plastic Surgery, 12334UT Southwestern, Dallas, TX, USA.,Analytical Imaging and Modeling Center, Children's Medical Center, Dallas, TX, USA
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Liu CYJ, Wilkinson C. Image conditions for machine-based face recognition of juvenile faces. Sci Justice 2020; 60:43-52. [PMID: 31924288 DOI: 10.1016/j.scijus.2019.10.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 08/06/2019] [Accepted: 10/06/2019] [Indexed: 11/27/2022]
Affiliation(s)
- Ching Yiu Jessica Liu
- Liverpool John Moores University, Liverpool School of Art and Design, IC1 Liverpool Science Park, 131 Mount Pleasant, Liverpool, Merseyside L3 5TF, United Kingdom.
| | - Caroline Wilkinson
- Liverpool John Moores University, Art and Design Academy, 2 Duckinfield Street, Liverpool, Merseyside L3 5RD, United Kingdom.
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Quantification of age-related changes in midsagittal facial profile using Fourier analysis: A longitudinal study on Japanese adult males. Forensic Sci Int 2019; 299:239.e1-239.e9. [DOI: 10.1016/j.forsciint.2019.04.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2018] [Revised: 04/04/2019] [Accepted: 04/05/2019] [Indexed: 11/22/2022]
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Uniform 3D meshes to establish normative facial averages of healthy infants during the first year of life. PLoS One 2019; 14:e0217267. [PMID: 31107914 PMCID: PMC6527206 DOI: 10.1371/journal.pone.0217267] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 05/01/2019] [Indexed: 11/21/2022] Open
Abstract
Three-dimensional (3D) surface imaging systems are replacing direct anthropometry as the preferred method for capturing facial soft-tissues. Aims of this study were: (1) to develop normative average 3D faces of healthy infants aged 3, 6, 9, and 12 months and (2) to describe normative average 3D facial growth data in infants aged 3 to 12 months. Three-dimensional images of 50 healthy children were acquired at 3, 6, 9, and 12 months of age using the 3dMDcranial system. Four average faces with uniform meshes (3, 6, 9, and 12 months) were developed and registered based on the children’s reference frames. Distance maps of growth of the total facial surface and of the nose, upper lip, chin, forehead and cheeks for the intervals 3 to 6 months, 6 to 9 months, and 9 to 12 months of age were calculated. Mean growth of the total facial surface was 3.9 mm (standard deviation [SD] 1.2 mm), 3.5 mm (SD 0.9 mm), and 1.6 mm (SD 0.7 mm) at 3 to 6 months, 6 to 9 months, and 9 to 12 months, respectively. Regarding the selected regions of the face, the mean growth of the nose and upper lip were the largest (3.7 mm and 3.6 mm, respectively) between 6 and 9 months of age. The mean growth of the forehead, cheeks and chin were the largest (5.4 mm, 3.2, and 4.7 mm, respectively) between 3 and 6 months of age. For all facial regions, growth clearly diminished from 9 to 12 months of age. Normative data on the growth of the full face, nose, upper lip, chin, forehead and cheeks are presented. Such data can be used in future studies to identify the effectiveness of treatment of orofacial deformities such as orofacial clefts during the first year of life.
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White JD, Ortega-Castrillón A, Matthews H, Zaidi AA, Ekrami O, Snyders J, Fan Y, Penington T, Van Dongen S, Shriver MD, Claes P. MeshMonk: Open-source large-scale intensive 3D phenotyping. Sci Rep 2019; 9:6085. [PMID: 30988365 PMCID: PMC6465282 DOI: 10.1038/s41598-019-42533-y] [Citation(s) in RCA: 76] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 03/29/2019] [Indexed: 01/26/2023] Open
Abstract
Dense surface registration, commonly used in computer science, could aid the biological sciences in accurate and comprehensive quantification of biological phenotypes. However, few toolboxes exist that are openly available, non-expert friendly, and validated in a way relevant to biologists. Here, we report a customizable toolbox for reproducible high-throughput dense phenotyping of 3D images, specifically geared towards biological use. Given a target image, a template is first oriented, repositioned, and scaled to the target during a scaled rigid registration step, then transformed further to fit the specific shape of the target using a non-rigid transformation. As validation, we use n = 41 3D facial images to demonstrate that the MeshMonk registration is accurate, with 1.26 mm average error, across 19 landmarks, between placements from manual observers and using the MeshMonk toolbox. We also report no variation in landmark position or centroid size significantly attributable to landmarking method used. Though validated using 19 landmarks, the MeshMonk toolbox produces a dense mesh of vertices across the entire surface, thus facilitating more comprehensive investigations of 3D shape variation. This expansion opens up exciting avenues of study in assessing biological shapes to better understand their phenotypic variation, genetic and developmental underpinnings, and evolutionary history.
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Affiliation(s)
- Julie D White
- Department of Anthropology, The Pennsylvania State University, University Park, PA, USA.
| | - Alejandra Ortega-Castrillón
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium
| | - Harold Matthews
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Pediatrics, University of Melbourne, Melbourne, Australia
- Department of Human Genetics, KU Leuven, Leuven, Belgium
| | - Arslan A Zaidi
- Department of Biology, The Pennsylvania State University, University Park, PA, USA
| | - Omid Ekrami
- Department of Biology, University of Antwerp, Antwerp, Belgium
| | | | - Yi Fan
- Murdoch Children's Research Institute, Melbourne, Australia
- Melbourne Dental School, University of Melbourne, Melbourne, Australia
| | - Tony Penington
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Pediatrics, University of Melbourne, Melbourne, Australia
- Royal Children's Hospital, Melbourne, Australia
| | | | - Mark D Shriver
- Department of Anthropology, The Pennsylvania State University, University Park, PA, USA
| | - Peter Claes
- Department of Electrical Engineering, ESAT/PSI, KU Leuven, Leuven, Belgium.
- Medical Imaging Research Center, UZ Leuven, Leuven, Belgium.
- Murdoch Children's Research Institute, Melbourne, Australia.
- Department of Human Genetics, KU Leuven, Leuven, Belgium.
- Department of Biomedical Engineering, University of Oxford, Oxford, United Kingdom.
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Ubelaker DH, Khosrowshahi H. Estimation of age in forensic anthropology: historical perspective and recent methodological advances. Forensic Sci Res 2019; 4:1-9. [PMID: 30915413 PMCID: PMC6427487 DOI: 10.1080/20961790.2018.1549711] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 10/10/2018] [Accepted: 11/14/2018] [Indexed: 01/30/2023] Open
Abstract
Estimation of age represents a central focus of forensic anthropological analysis of human skeletal remains and of the living. Advances registered in recent research include the topics of taphonomic impact, new anatomical areas of interest, histology, population variation, the dental pulp chamber, technology, mathematical approaches, biochemical analysis and techniques specifically targeting the living. This article reviews the historical development of age estimation methods and considers likely future directions.
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Affiliation(s)
- Douglas H Ubelaker
- Department of Anthropology, Smithsonian Institution, Washington, DC, USA
| | - Haley Khosrowshahi
- Department of Anthropology, Smithsonian Institution, Washington, DC, USA
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12
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Koudelová J, Hoffmannová E, Dupej J, Velemínská J. Simulation of facial growth based on longitudinal data: Age progression and age regression between 7 and 17 years of age using 3D surface data. PLoS One 2019; 14:e0212618. [PMID: 30794623 PMCID: PMC6386244 DOI: 10.1371/journal.pone.0212618] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Accepted: 02/06/2019] [Indexed: 12/03/2022] Open
Abstract
Modelling of the development of facial morphology during childhood and adolescence is highly useful in forensic and biomedical practice. However, most studies in this area fail to capture the essence of the face as a three-dimensional structure. The main aims of our present study were (1) to construct ageing trajectories for the female and male face between 7 and 17 years of age and (2) to propose a three-dimensional age progression (age -regression) system focused on real growth-related facial changes. Our approach was based on an assessment of a total of 522 three-dimensional (3D) facial scans of Czech children (39 boys, 48 girls) that were longitudinally studied between the ages of 7 to 12 and 12 to 17 years. Facial surface scans were obtained using a Vectra-3D scanner and evaluated using geometric morphometric methods (CPD-DCA, PCA, Hotelling’s T2 tests). We observed very similar growth rates between 7 and 10 years in both sexes, followed by an increase in growth velocity in both sexes, with maxima between 11 and 12 years in girls and 11 to 13 years in boys, which are connected with the different timing of the onset of puberty. Based on these partly different ageing trajectories for girls and boys, we simulated the effects of age progression (age regression) on facial scans. In girls, the mean error was 1.81 mm at 12 years and 1.7 mm at 17 years. In boys, the prediction system was slightly less successful: 2.0 mm at 12 years and 1.94 mm at 17 years. The areas with the greatest deviations between predicted and real facial morphology were not important for facial recognition. Changes of body mass index percentiles in children throughout the observation period had no significant influence on the accuracy of the age progression models for both sexes.
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Affiliation(s)
- Jana Koudelová
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
- * E-mail:
| | - Eva Hoffmannová
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
| | - Ján Dupej
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
- Department of Software and Computer Science, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic
| | - Jana Velemínská
- Department of Anthropology and Human Genetics, Faculty of Science, Charles University, Prague, Czech Republic
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13
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Stephan CN, Caple JM, Guyomarc’h P, Claes P. An overview of the latest developments in facial imaging. Forensic Sci Res 2018; 4:10-28. [PMID: 30915414 PMCID: PMC6427692 DOI: 10.1080/20961790.2018.1519892] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 09/02/2018] [Accepted: 09/03/2018] [Indexed: 10/30/2022] Open
Abstract
Facial imaging is a term used to describe methods that use facial images to assist or facilitate human identification. This pertains to two craniofacial identification procedures that use skulls and faces-facial approximation and photographic superimposition-as well as face-only methods for age progression/regression, the construction of facial graphics from eyewitness memory (including composites and artistic sketches), facial depiction, face mapping and newly emerging methods of molecular photofitting. Given the breadth of these facial imaging techniques, it is not surprising that a broad array of subject-matter experts participate in and/or contribute to the formulation and implementation of these methods (including forensic odontologists, forensic artists, police officers, electrical engineers, anatomists, geneticists, medical image specialists, psychologists, computer graphic programmers and software developers). As they are concerned with the physical characteristics of humans, each of these facial imaging areas also falls in the domain of physical anthropology, although not all of them have been traditionally regarded as such. This too offers useful opportunities to adapt established methods in one domain to others more traditionally held to be disciplines within physical anthropology (e.g. facial approximation, craniofacial superimposition and face photo-comparison). It is important to note that most facial imaging methods are not currently used for identification but serve to assist authorities in narrowing or directing investigations such that other, more potent, methods of identification can be used (e.g. DNA). Few, if any, facial imaging approaches can be considered honed end-stage scientific methods, with major opportunities for physical anthropologists to make meaningful contributions. Some facial imaging methods have considerably stronger scientific underpinnings than others (e.g. facial approximation versus face mapping), some currently lie entirely within the artistic sphere (facial depiction), and yet others are so aspirational that realistic capacity to obtain their aims has strongly been questioned despite highly advanced technical approaches (molecular photofitting). All this makes for a broad-ranging, dynamic and energetic field that is in a constant state of flux. This manuscript provides a theoretical snapshot of the purposes of these methods, the state of science as it pertains to them, and their latest research developments.
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Affiliation(s)
- Carl N. Stephan
- Laboratory for Human Craniofacial and Skeletal Identification (HuCS-ID Lab), School of Biomedical Sciences, The University of Queensland, St Lucia, Australia
| | - Jodi M. Caple
- Laboratory for Human Craniofacial and Skeletal Identification (HuCS-ID Lab), School of Biomedical Sciences, The University of Queensland, St Lucia, Australia
| | - Pierre Guyomarc’h
- Unite Mixte de Recherche (UMR) 5199 De la Préhistoire à l'Actuel: Culture, Environnement et Anthropologie (PACEA), Ministère de la Culture et de la Communication (MCC), Centre National de la Recherche Scientifique (CNRS), Université de Bordeaux, Pessac, France
| | - Peter Claes
- Department of Electrical Engineering, Department of Electrical Engineering (ESAT)/Processing of Speech and Images (PSI), KU Leuven, Leuven, Belgium
- Medical Imaging Research Center (MIRC), Universitair Ziekenhuis, Leuven, Belgium
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