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Age Estimation Using 3D Shape of the Face

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Computer Vision, Imaging and Computer Graphics - Theory and Applications (VISIGRAPP 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 550))

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Abstract

The 3D shape of human faces deform with time and contain rich aging information. However, in the literature, no work has been done with the 3D shape of face for age estimation. Thus, we propose in this paper to explore the 3D facial surface in age estimation. Based on Riemannian shape analysis of facial curves, we extract four types of Dense Scalar Field (DSF) descriptions from the 3D facial surface, which reflect the face Averageness, face Symmetry, and the Spatial and Gradient deviations of the face. Experiments are carried out following the Leave-One-Person-Out (LOPO) cross-validation on the earliest 466 scans in FRGCv2 dataset, using the Random Forest Regressor. With the DSF features, the proposed approach achieves 3.29 years Mean Absolute Error (MAE) in the gender-general experiments, and 3.15 years MAE in the gender-specific experiments. Results confirm the idea that the face aging differs with gender. To address the high dimensionality of DSF features and the imbalance in training instances, we propose to use a weighted PCA method. In both the gender-general and gender-specific experiments, the age estimation performances using weighted PCA are comparable to the performances using the DSF descriptions. While, the size of feature is significantly smaller with the weighted PCA.

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Authors and Affiliations

  1. Télécom Lille/LIFL (UMR CNRS 8022), Cité Scientifique, Villeneuve D’ascq, France

    Baiqiang Xia, Boulbaba Ben Amor & Mohamed Daoudi

Authors
  1. Baiqiang Xia
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  2. Boulbaba Ben Amor
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  3. Mohamed Daoudi
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Corresponding author

Correspondence to Baiqiang Xia .

Editor information

Editors and Affiliations

  1. Dip. di Matematica e Informatica, Università di Catania, Catania, Catania, Italy

    Sebastiano Battiato

  2. Inria/ZIRST, Saint Ismier, France

    Sabine Coquillart

  3. INRIA-Rennes/MimeTIC Tean, Rennes cedex, France

    Julien Pettré

  4. Swansea University, Swansea, UK

    Robert S. Laramee

  5. Computer Science, Linnaeus University, Växjö, Sweden

    Andreas Kerren

  6. do IPS, Escola Superior de Tecnologia, Setúbal, Portugal

    José Braz

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Xia, B., Amor, B.B., Daoudi, M. (2015). Age Estimation Using 3D Shape of the Face. In: Battiato, S., Coquillart, S., Pettré, J., Laramee, R., Kerren, A., Braz, J. (eds) Computer Vision, Imaging and Computer Graphics - Theory and Applications. VISIGRAPP 2014. Communications in Computer and Information Science, vol 550. Springer, Cham. https://doi.org/10.1007/978-3-319-25117-2_11

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  • DOI: https://doi.org/10.1007/978-3-319-25117-2_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25116-5

  • Online ISBN: 978-3-319-25117-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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