Simulation of facial growth based on longitudinal data: Age progression and age regression between 7 and 17 years of age using 3D surface data

. 2019 ; 14 (2) : e0212618. [epub] 20190222

Jazyk angličtina Země Spojené státy americké Médium electronic-ecollection

Typ dokumentu klinické zkoušky, časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/pmid30794623

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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Scheffler C. Variable and invariable proportions in the ontogenesis of the human face. J Craniofac Surg. 2013;24(1):237–41. 10.1097/SCS.0b013e31826d07a3 PubMed DOI

Mallett XDG, Dryden I, Vorder Bruegge R, Evison M. An Exploration of Sample Representativeness in Anthropometric Facial Comparison. J Forensic Sci. 2010;55(4):1025–31. 10.1111/j.1556-4029.2010.01425.x PubMed DOI

Ritz-Timme S, Cattaneo C, Collins MJ, Waite ER, Schütz HW, Kaatsch HJ, et al. Age estimation: the state of the art in relation to the specific demands of forensic practise. Int J Legal Med. 2000;113(3):129–36. PubMed

International Commission on Missing Persons [Internet]. http://www.ic-mp.org/

International Organization for Migration [Internet]. https://www.iom.int/

National centre for Missing and Exploited Children [Internet]. http://www.missingkids.com/

Missing Children Europe [Internet]. http://missingchildreneurope.eu/

Home | Europol [Internet]. https://www.europol.europa.eu/

Lampinen JM, Miller JT, Dehon H. Depicting the Missing: Prospective and Retrospective Person Memory for Age Progressed Images. Appl Cogn Psychol. 2012;26(2):167–73.

Cunha E, Baccino E, Martrille L, Ramsthaler F, Prieto J, Schuliar Y, et al. The problem of aging human remains and living individuals: A review. Forensic Sci Int. 2009;193(1–3):1–13. 10.1016/j.forsciint.2009.09.008 PubMed DOI

Scandrett (née Hill) CM, Solomon CJ, Gibson SJ. A person-specific, rigorous aging model of the human face. Pattern Recognition Lett. 2006;27:1776–1787.

Charman SD, Carol RN. Age-progressed images may harm recognition of missing children by increasing the number of plausible targets. J Appl Res Mem Cogn. 2012;1(3):171–8.

Gibson SJ, Scandrett CM, Solomon CJ, Maylin MIS, Wilkinson CM. Computer assisted age progression. Forensic Sci Med Pathol. 2009;5(3):174–81. 10.1007/s12024-009-9102-z PubMed DOI

Shu X, Tang J, Lai H, Liu L, Yan S. Personalized Age Progression with Aging Dictionary. In: IEEE Trans Pattern Anal Mach Intell. 2018;40(4):905–917. PubMed

Liu S, Sun Y, Zhu D, Bao R, Wang W, Shu X, et al. Face Aging with Contextual Generative Adversarial Nets. Proceedings of the 2017 ACM on Multimedia Conference. 2017;pp:82–90.

Duong CN, Quach KG, Luu K, le THN, Savvides M. Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition. In: IEEE I Conf Comp Vis. 2017;pp:3755–63.

Yang H, Member S, Huang D, Wang Y, Wang H, Tang Y. Face Aging Effect Simulation using Hidden Factor Analysis Joint Sparse Representation. In: IEEE T Image Process. 2016;25(6):2493–07. PubMed

Machado CEP, Flores MRP, Lima LNC, Tinoco RLR, Franco A, Bezerra ACB, et al. A new approach for the analysis of facial growth and age estimation: Iris ratio. PLoS One. 2017;12(7):e0180330 10.1371/journal.pone.0180330 PubMed DOI PMC

Caplova Z, Compassi V, Giancola S, Gibelli DM, Obertová Z, Poppa P, et al. Recognition of children on age-different images: Facial morphology and age-stable features. Sci Justice. 2017;57(4):250–6. 10.1016/j.scijus.2017.03.005 PubMed DOI

Lampinen JM, Erickson WB, Frowd C, Michael J, Erickson WB, Frowd C. Mighty Morphin ‘ age progression: how artist, age range, and morphing influences the similarity of forensic age progressions to target individuals. Psychol Crime Law. 2015;21(10):952–967.

Green MA, Evison MP. Interpolating Between Computerized Three-Dimensional Forensic Facial Simulations. J Forensic Sci. 1999;44(6):14591J.

Evison MP, Green MA. Presenting Three-Dimensional Forensic Facial Simulations on the Internet Using VRML. J Forensic Sci. 1999;44(6):14590J.

Koudelová J, Dupej J, Brůžek J, Sedlak P, Velemínská J. Modelling of facial growth in Czech children based on longitudinal data: Age progression from 12 to 15 years using 3D surface models. Forensic Sci Int. 2015;248:33–40. 10.1016/j.forsciint.2014.12.005 PubMed DOI

Mydlová M, Dupej J, Koudelová J, Velemínská J. Sexual dimorphism of facial appearance in ageing human adults: A cross-sectional study. Forensic Sci Int. 2015;257:519.e1–e9. PubMed

Matthews H, Penington A, Clement J, Kilpatrick N, Fan Y, Claes P. Estimating age and synthesising growth in children and adolescents using 3D facial prototypes. Forensic Sci Int. 2018;286:61–9. 10.1016/j.forsciint.2018.02.024 PubMed DOI

Fu Y, Guo G, Huang TS. Age synthesis and estimation via faces: A survey. IEEE Trans Pattern Anal Mach Intell. 2010;32(11):1955–76. 10.1109/TPAMI.2010.36 PubMed DOI

Hutton TJ, Buxton BF, Hammond P, Potts HWW. Estimating average growth trajectories in shape-space using kernel smoothing. IEEE Trans Med Imaging. 2003;22(6):747–53. 10.1109/TMI.2003.814784 PubMed DOI

Enlow DH, Hans MG. Essentials of facial growth. Philadelphia: Saunders; 1996.

Freidline SE, Gunz P, Hublin J-J. Ontogenetic and static allometry in the human face: Contrasting Khoisan and Inuit. Am J Phys Anthropol. 2015;158(1):116–31. 10.1002/ajpa.22759 PubMed DOI

Windhager S, Patocka K, Schaefer K. Body fat and facial shape are correlated in female adolescents. Am J Hum Biol. 2013;25(6):847–50. 10.1002/ajhb.22444 PubMed DOI

Ferrario VF, Dellavia C, Tartaglia GM, Turci M, Sforza C. Soft Tissue Facial Morphology in Obese Adolescents: A Three-Dimensional Noninvasive Assessment. Angle Orthod. 2004;74(1):37–42. 10.1043/0003-3219(2004)074<0037:STFMIO>2.0.CO;2 PubMed DOI

Coetzee V, Perrett DI, Stephen ID. Facial Adiposity: A Cue to Health? Perception. 2009;38(11):1700–11. 10.1068/p6423 PubMed DOI

Cole TJ, Faith MS, Pietrobelli A, Heo M. What is the best measure of adiposity change in growing children: BMI, BMI %, BMI z-score or BMI centile? Eur J Clin Nutr. 2005;59(3):419–25. 10.1038/sj.ejcn.1602090 PubMed DOI

Cole TJ, Freeman J V, Preece MA. British 1990 growth reference centiles for weight, height, body mass index and head circumference fitted by maximum penalized likelihood. Stat Med. 1998;17(4):407–29. PubMed

Sedlak P, Pařízková J, Daniš R, Dvořáková H, Vignerová J. Secular Changes of Adiposity and Motor Development in Czech Preschool Children: Lifestyle Changes in Fifty-Five Year Retrospective Study. Biomed Res Int. 2015;2015:1–9. PubMed PMC

Vignerová J, Humeníkova L, Brabec M, Riedlová J, Bláha P. Long-term changes in body weight, BMI, and adiposity rebound among children and adolescents in the Czech republic. Econ Hum Biol. 2007;5(3):409–25. 10.1016/j.ehb.2007.07.003 PubMed DOI

Dupej J, Krajíček V, Velemínská J, Pelikán J. Statistical Mesh Shape Analysis with Nonlandmark Nonrigid Registration. In: Eurographics Symposium on Geometry Processing. 2014.

Morphome3cs II [Internet]. http://www.morphome3cs.com/

Vignerová J. Růst CZ—nový software pro hodnocení růstu dětí. Pediatr pro praxi. 2006;7(3):171.

Cattaneo C, Obertová Z, Ratnayake M, Marasciuolo L, Tutkuviene J, Poppa P, et al. Can facial proportions taken from images be of use for ageing in cases of suspected child pornography? A pilot study. Int J Legal Med. 2012;126(1):139–44. 10.1007/s00414-011-0564-7 PubMed DOI

Ratnayake M, Obertová Z, Dose M, Gabriel P, Bröker HM, Brauckmann M, et al. The juvenile face as a suitable age indicator in child pornography cases: a pilot study on the reliability of automated and visual estimation approaches. Int J Legal Med. 2014;128:803–8. 10.1007/s00414-013-0875-y PubMed DOI

Cattaneo C, Ritz-Timme S, Gabriel P, Gibelli D, Giudici E, Poppa P, et al. The difficult issue of age assessment on pedo-pornographic material. Forensic Sci Int. 2009;183(1–3):e21–4. 10.1016/j.forsciint.2008.09.005 PubMed DOI

Cardenas-Esguerra M, Vidal C, Cavalcante-Neto JB, Vieira R. Facial aging simulation applied to the missing person problem. In: Inform CLEI 2012 XXXVIII Conf Latinoam En. 2012.

Geng X, Zhou Z-H, Zhang Y, Li G, Dai H. Learning from facial aging patterns for automatic age estimation. In: ACM Press. 2006; p. 307.

Liu J, Ma Y, Duan L, Wang F, Liu Y. Hybrid constraint SVR for facial age estimation. Signal Processing. 2014;94:576–82.

Ramanathan N, Chellappa R. Modeling Age Progression in Young Faces. In: Proc IEEE Conf Computer Vision and Pattern Recognition; 2006; pp. 387–94.

Kittler J, Hilton A, Hamouz M, Illingworth J. 3D Assisted Face Recognition: A Survey of 3D Imaging, Modelling and Recognition Approachest. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR’05)—Workshops. 2005.

Suwajanakorn S, Kemelmacher-Shlizerman I, Seitz SM. Total Moving Face Reconstruction. In Springer, Cham: 2014; pp. 796–812.

Jin H, Wang X, Zhong Z, Hua J. Robust 3D face modeling and reconstruction from frontal and side images. Comput Aided Geom Des. 2017;50:1–13.

Erickson WB, Lampinen JM, Frowd CD, Mahoney G. When age-progressed images are unreliable: The roles of external features and age range. Sci Justice. 2017;57(2):136–43. 10.1016/j.scijus.2016.11.006 PubMed DOI

Bulygina E, Mitteroecker P, Aiello L. Ontogeny of facial dimorphism and patterns of individual development within one human population. Am J Phys Anthropol. 2006;131(3):432–43. 10.1002/ajpa.20317 PubMed DOI

Velemínská J, Bigoni L, Krajíček V, Borský J, Šmahelová D, Cagáňová V, et al. Surface facial modelling and allometry in relation to sexual dimorphism. HOMO—J Comp Hum Biol. 2012;63(2):81–93. PubMed

Ferrario VF, Sforza C, Poggio CE, Schmitz JH. Soft-tissue facial morphometry from 6 years to adulthood: a three-dimensional growth study using a new modeling. Plast Reconstr Surg. 1999;103(3):768–78. PubMed

Ferrario VF, Sforza C, Serrao G, Ciusa V, Dellavia C. Growth and aging of facial soft tissues: A computerized three-dimensional mesh diagram analysis. Clin Anat. 2003;16(5):420–33. PubMed

Nute SJ, Moss JP. Three-dimensional facial growth studied by optical surface scanning. J Orthod. 2000;27(1):31–8. 10.1093/ortho/27.1.31 PubMed DOI

Djordjevic J, Pirttiniemi P, Harila V, Heikkinen T, Toma AM, Zhurov AI, et al. Three-dimensional longitudinal assessment of facial symmetry in adolescents. Eur J Orthod. 2013;35(2):143–51. 10.1093/ejo/cjr006 PubMed DOI

Kau CH, Richmond S. Three-dimensional analysis of facial morphology surface changes in untreated children from 12 to 14 years of age. Am J Orthod Dentofac Orthop. 2008;134(6):751–60. PubMed

Bergman RT, Waschak J, Borzabadi-Farahani A, Murphy NC. Longitudinal study of cephalometric soft tissue profile traits between the ages of 6 and 18 years. Angle Orthod. 2014; 84(1):48–55. 10.2319/041513-291.1 PubMed DOI PMC

Matthews HS, Penington AJ, Hardiman R, Fan Y, Clement JG, Kilpatrick NM, et al. Modelling 3D craniofacial growth trajectories for population comparison and classification illustrated using sex-differences. Sci Rep. 2018;8(1):4771 10.1038/s41598-018-22752-5 PubMed DOI PMC

Primozic J, Perinetti G, Contardo L, Ovsenik M. Facial soft tissue changes during the pre-pubertal and pubertal growth phase: a mixed longitudinal laser-scanning study. Eur J Orthod. 2017;39(1):52–60. 10.1093/ejo/cjw008 PubMed DOI

Mitteroecker P, Gunz P, Windhager S, Schaefer K. A brief review of shape, form, and allometry in geometric morphometrics, with applications to human facial morphology. Hystrix It J Mamm. 2013;24(1):59–66.

Longmore CA, Liu CH, Young AW. The importance of internal facial features in learning new faces. Q J Exp Psychol. 2015;68(2):249–60. PubMed

Tome P, Fierrez J, Vera-Rodriguez R, Ramos D. Identification using face regions: Application and assessment in forensic scenarios. Forensic Sci Int. 2013;233(1–3):75–83. 10.1016/j.forsciint.2013.08.020 PubMed DOI

Axelrod V, Yovel G. External facial features modify the representation of internal facial features in the fusiform face area. Neuroimage. 2010;52(2):720–5. 10.1016/j.neuroimage.2010.04.027 PubMed DOI

Freedman DS, Wang J, Maynard LM, Thornton JC, Mei Z, Pierson RN, et al. Relation of BMI to fat and fat-free mass among children and adolescents. Int J Obes. 2005;29(1):1–8. PubMed

Hodges-Simeon CR, Hanson Sobraske KN, Samore T, Gurven M, Gaulin SJC. Facial Width-To-Height Ratio (fWHR) Is Not Associated with Adolescent Testosterone Levels. PLoS One. 2016;11(4):e0153083 10.1371/journal.pone.0153083 PubMed DOI PMC

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