Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben
Erschienen in:
A Comprehensive Introduction to Photometric 3D-Reconstruction Kapitel lesen Erstes Kapitel lesen

2020 | OriginalPaper | Buchkapitel

7. Estimating Facial Aging Using Light Scattering Photometry

verfasst von : Hadi A. Dahlan, Edwin R. Hancock

Erschienen in: Advances in Photometric 3D-Reconstruction

Verlag: Springer International Publishing

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Facial aging is a complex process, and the changes in the inner layers of the skin will affect how the light scatters from the skin. To observe whether a light scattering model parameter is suitable to be used for age classification/estimation, this study investigated and analyzed the relationship between the parameter of an analytical-based light scattering model and skins of various ages using photometry method. Multiple models are used to investigate and compare the relationship between the model parameters and the subject’s age. The results show that all of the models’ roughness parameter representation has a significant positive correlation with age (\(p<0.05\)), making it a suitable choice to be made as a feature for estimating/classifying age. This study proves that the parameter(s) for an analytical-based light scattering model can be used as an alternative method for estimating/classifying a person’s age, provided that we know the light incidence and reflectance angles. In the future, this method can be used to work with other age extractors/estimators/classifiers, for the purpose of designing a more robust age estimation/classification method.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Jetzt informieren
Vorheriges Kapitel Recent Progress in Shape from Polarization
Literatur
1.
Fu Y, Guo G, Huang TS (2010) Age synthesis and estimation via faces: a survey. IEEE Trans Pattern Anal Mach Intell 32(11):1955–1976
2.
Ramanathan N, Chellappa R (2006) Modeling age progression in young faces. In: 2006 IEEE computer society conference on computer vision and pattern recognition, vol 1. IEEE
3.
Rhodes MG (2009) Age estimation of faces: a review. Appl Cognit Psychol 23(1):1–12
4.
Fink B et al (2011) Differences in visual perception of age and attractiveness of female facial and body skin. Inter J Cosmetic Sci 33(2): 26–131
5.
Fink B, Grammer K, Matts PJ (2006) Visible skin color distribution plays a role in the perception of age, attractiveness, and health in female faces. Evol Human Behav 27(6):433–442
6.
Zimbler MS, Kokoska MS, Regan Thomas J (2001) Anatomy and pathophysiology of facial aging. Facial Plastic Surg Clin North Am 9(2):179–187
7.
Igarashi T, Nishino K, Nayar SK (2007) The appearance of human skin: a survey. Found Trends Comput Graph Vis 3(1):1–95
8.
Ramanathan N, Chellappa R, Biswas S (2009) Age progression in human faces: a survey. J Vis Lang Comput 15:3349–3361
9.
Ramanathan N, Chellappa R, Biswas S (2009) Computational methods for modeling facial aging: a survey. J Vis Lang Comput 20(3):131–144
10.
Anderson RR, Parrish JA (1981) The optics of human skin. J Invest Dermatol 77(1):13–19
11.
Anderson RR, Parrish JA (1982) Optical properties of human skin. In: The science of photomedicine. Springer, Boston, pp 147–194
12.
Neerken S, et al (2004) Characterization of age-related effects in human skin: a comparative study that applies confocal laser scanning microscopy and optical coherence tomography. J Biomed Optics 9(2):274–282
13.
O’Toole AJ, et al (1999) 3D shape and 2D surface textures of human faces: the role of “averages” in attractiveness and age. Image Visi Comput 18(1):9–19
14.
Liu Z, Zhang Z, Shan Y (2004) Image-based surface detail transfer. IEEE Comput Graph Appl 24(3):30–35
15.
Vetter T (1998) Synthesis of novel views from a single face image. Int J Comput Vis 28(2):103–116MathSciNet
16.
Golovinskiy A, et al (2006) A statistical model for synthesis of detailed facial geometry. ACM Trans Graph (TOG) 25(3):1025–1034
17.
Patterson E, et al (2007) Aspects of age variation in facial morphology affecting biometrics. In: BTAS 2007. First IEEE international conference on biometrics: theory, applications, and systems, 2007. IEEE
18.
Kwon YH, da Vitoria Lobo N (1999) Age classification from facial images. Comput Vis Image Underst 74(1):1–21
19.
Geng X, Zhou Z-H, Smith-Miles K (2007) Automatic age estimation based on facial aging patterns. IEEE Trans Pattern Anal Mach Intell 29(12):2234–2240
20.
Fu Y, Xu Y, Huang TS (2007) Estimating human age by manifold analysis of face pictures and regression on aging features. In: 2007 IEEE international conference on multimedia and expo. IEEE
21.
Choi SE, et al (2011) Age estimation using a hierarchical classifier based on global and local facial features. Pattern Recognit 44(6):1262–1281
22.
Han H, et al (2015) Demographic estimation from face images: human vs. machine performance. IEEE Trans Pattern Anal Mach Intell 37(6):1148–1161
23.
Montes Soldado R, Ureña Almagro C (2012) An overview of BRDF models
24.
Forsyth DA, Ponce J (2012) Computer vision: a modern approach, 2nd edn. Pearson, London
25.
Wynn C (2000) An introduction to BRDF-based lighting. Nvidia Corporation
26.
Hanrahan P, Krueger W (1993) Reflection from layered surfaces due to subsurface scattering. In: Proceedings of the 20th annual conference on computer graphics and interactive techniques. ACM
27.
Koenderink J, Pont S (2003) The secret of velvety skin. Mach Vis Appl 14(4):260–268
28.
Tsumura N, et al (2003) Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin. ACM Trans Graph (TOG) 22(3):770–779
29.
Krishnaswamy A, Baranoski GVG (2004) A biophysically-based spectral model of light interaction with human skin. In: Computer graphics forum, vol 23. No. 3. Blackwell Publishing, Inc, Malden
30.
Iglesias–Guitian JA, et al (2015) A biophysically-based model of the optical properties of skin aging. Comput Graph Forum 34(2)
31.
Weyrich T, et al (2006) Analysis of human faces using a measurement-based skin reflectance model. ACM Trans Graph (TOG). vol 25. No. 3. ACM
32.
Donner C, Jensen HW (2006) A spectral BSSRDF for shading human skin. Rendering techniques 2006, pp 409–418
33.
Donner C, et al (2008) A layered, heterogeneous reflectance model for acquiring and rendering human skin. ACM Trans Graph (TOG), vol. 27. No. 5. ACM
34.
Ma W-C, et al. (2007) Rapid acquisition of specular and diffuse normal maps from polarized spherical gradient illumination. In: Proceedings of the 18th Eurographics conference on rendering techniques. Eurographics Association
35.
Ragheb H, Hancock ER (2008) A light scattering model for layered dielectrics with rough surface boundaries. Int J Comput Vis 79(2):179–207
36.
Dahlan HA, Hancock ER (2016) Absorptive scattering model for rough laminar surfaces. In: 2016 23rd international conference on pattern recognition (ICPR). IEEE
37.
Oren M, Nayar SK (1994) Generalization of Lambert’s reflectance model. In: Proceedings of the 21st annual conference on computer graphics and interactive techniques
38.
Jensen HW, et al (2001) A practical model for subsurface light transport. In: Proceedings of the 28th annual conference on computer graphics and interactive techniques. ACM
39.
Dutta A (2010) Face shape and reflectance acquisition using a multispectral light stage. University of York, Diss
40.
Fitzpatrick TB (1988) The validity and practicality of sun-reactive skin types I through VI. Archives of dermatology, vol. 124. No. 6. American Medical Association, pp 869–871
41.
Dahlan HA, Hancock ER, Smith WAP (2016) Reflectance-aware optical flow. In: 2016 23rd international conference on pattern recognition (ICPR). IEEE
42.
Shirakabe Y, Suzuki Y, Lam SM (2003) A new paradigm for the aging Asian face. Aesthetic Plast Surg 27(5):397–402
43.
Liew S, et al (2016) Consensus on changing trends, attitudes, and concepts of Asian beauty. Aesthetic Plast Surg 40(2):193–201
44.
Vashi NA, De Castro Maymone MB, Kundu RV (2016) Aging differences in ethnic skin. J Clin Aesthetic Dermatol 9(1):31
45.
Talakoub L, Wesley NO (2009) Differences in perceptions of beauty and cosmetic procedures performed in ethnic patients. Seminars in cutaneous medicine and surgery, vol 28. No 2. Frontline Medical Communications
46.
Rawlings AV (2006) Ethnic skin types: are there differences in skin structure and function? Int J Cosmet Sci 28(2):79–93MathSciNet
47.
Fink B et al (2012) Colour homogeneity and visual perception of age, health and attractiveness of male facial skin. J Eur Acad Dermatol Venereol 26(12):1486–1492
48.
Matts PJ, et al (2007) Color homogeneity and visual perception of age, health, and attractiveness of female facial skin. J Am Acad Dermatol 57(6):977–984
49.
Vapnik V (2013) The nature of statistical learning theory. Springer Science & Business Media, Berlin
50.
Calin MA, Parasca SV (2010) In vivo study of age-related changes in the optical properties of the skin. Lasers Med Sci 25(2):269–274
Metadaten
Titel
Estimating Facial Aging Using Light Scattering Photometry
verfasst von
Hadi A. Dahlan
Edwin R. Hancock
Copyright-Jahr
2020
Buch
Advances in Photometric 3D-Reconstruction

Print ISBN: 978-3-030-51865-3

Electronic ISBN: 978-3-030-51866-0

Copyright-Jahr: 2020

DOI
https://doi.org/10.1007/978-3-030-51866-0_7

Premium Partner

    Bildnachweise