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Computation of facial attractiveness from 3D geometry

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Abstract

The face attractiveness from 3D representation is still in the infancy stage. In this paper, we investigate the role of 3D face geometry in facial beauty perception. Driven by heuristic rules, the aesthetics-aware geometric features are extracted, including features directly extended from 2D task to the 3D space, i.e., the global shape and Euclidean ratios, as well as features exclusively designed for 3D face structure, i.e., the geodesic ratios and region-based curvatures. A benchmark dataset with face models and attractiveness ratings is developed for facial attractiveness computation. Experimental results demonstrate the significance of 3D geometric features in capturing the face geometry over their 2D counterparts, and the advantages of the exclusive features in characterizing facial attractiveness over the extended features.

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Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 61902435, in part by Hunan Provincial Natural Science Foundation of China under Grant 2019JJ50808, and in part by the Fundamental Research Funds for the Central Universities of Central South University.

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Authors and Affiliations

  1. School of Computer Science and Engineering, Central South University, Changsha, 410083, Hunan, China

    Shu Liu, Enquan Huang, Yan Xu & Kexuan Wang

  2. Hunan Engineering Research Center of Machine Vision and Intelligent Medicine, Changsha, 410083, Hunan, China

    Shu Liu, Enquan Huang, Yan Xu & Kexuan Wang

  3. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Deepak Kumar Jain

Authors
  1. Shu Liu
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  2. Enquan Huang
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  3. Yan Xu
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  4. Kexuan Wang
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  5. Deepak Kumar Jain
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Corresponding author

Correspondence to Kexuan Wang.

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Liu, S., Huang, E., Xu, Y. et al. Computation of facial attractiveness from 3D geometry. Soft Comput 26, 10401–10407 (2022). https://doi.org/10.1007/s00500-022-07324-0

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  • DOI: https://doi.org/10.1007/s00500-022-07324-0

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