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Estimating Facial Aging Using Light Scattering Photometry

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Advances in Photometric 3D-Reconstruction

Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

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.

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Author information

Authors and Affiliations

  1. Faculty of Information Science and Technology, The National University of Malaysia, 43600 UKM, Bangi, Selangor, Malaysia

    Hadi A. Dahlan

  2. Department of Computer Science, University of York, Deramore Lane, York, YO10 5GH, UK

    Edwin R. Hancock

Authors
  1. Hadi A. Dahlan
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  2. Edwin R. Hancock
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Correspondence to Hadi A. Dahlan .

Editor information

Editors and Affiliations

  1. IRIT, UMR CNRS 5505, University of Toulouse, Toulouse, France

    Jean-Denis Durou

  2. Department of Mathematics, Sapienza University of Rome, Rome, Italy

    Maurizio Falcone

  3. GREYC Laboratory, CNRS, Caen, France

    Yvain Quéau

  4. Department of Mathematics and Applications “Renato Caccioppoli”, University of Naples Federico II, Naples, Italy

    Silvia Tozza

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Dahlan, H.A., Hancock, E.R. (2020). Estimating Facial Aging Using Light Scattering Photometry. In: Durou, JD., Falcone, M., Quéau, Y., Tozza, S. (eds) Advances in Photometric 3D-Reconstruction. Advances in Computer Vision and Pattern Recognition. Springer, Cham. https://doi.org/10.1007/978-3-030-51866-0_7

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

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-51865-3

  • Online ISBN: 978-3-030-51866-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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