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A Brief Review of 3D Face Reconstruction Methods for Face-Related Product Design

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Convergence of Ergonomics and Design (ACEDSEANES 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1298))

Abstract

3D face reconstruction is highly important in the ergonomics study of 3D face, especially in terms of designing face-related products. With the development of machine vision and deep learning, it becomes feasible to reconstruct the 3D face from a single image, which can make it practical to obtain a large scale data of 3D face shape instead of using the 3D scanning technology. The 3D face reconstruction methods, to recover the 3D facial geometry under unconstrained situations from 2D images, are roughly classified into two categories, namely (1) 3D Morphable Model (3DMM) fitting based method and (2) End-to-end deep convolutional neural network (CNN) based method. The 3DMM as a general face representation is introduced emphatically and two kinds of 3DMM fitting based methods are introduced when improving the 3DMM modeling mechanism. Four representative CNN based methods are compared when regressing from pixels of face image to the 3D face coordinates in different gird-like data structures. Finally, six common face datasets largely used in the training and testing are listed.

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Acknowledgement

This work was supported by The Hong Kong Research Grants Council (RGC PolyU. 15603419).

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Authors and Affiliations

  1. School of Design, The Hong Kong Polytechnic University, Hong Kong SAR, China

    Jie Zhang & Yan Luximon

  2. School of Computer and Communication Engineering, University of Science and Technology, Beijing, China

    Kangneng Zhou

Authors
  1. Jie Zhang
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  2. Kangneng Zhou
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  3. Yan Luximon
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Corresponding author

Correspondence to Yan Luximon .

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Editors and Affiliations

  1. Industrial and Systems Engineering, John Gokongwei Jr. College of Engineering, De La Salle University, Manila, Philippines

    Alma Maria Jennifer Gutierrez

  2. Department of Industrial Engineering and Decision Analytics, Hong Kong University of Science and Technology, Hong Kong, Hong Kong

    Ravindra S. Goonetilleke

  3. Mapúa University, Manila, Philippines

    Rex Aurellius C. Robielos

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Zhang, J., Zhou, K., Luximon, Y. (2021). A Brief Review of 3D Face Reconstruction Methods for Face-Related Product Design. In: Gutierrez, A.M.J., Goonetilleke, R.S., Robielos, R.A.C. (eds) Convergence of Ergonomics and Design. ACEDSEANES 2020. Advances in Intelligent Systems and Computing, vol 1298. Springer, Cham. https://doi.org/10.1007/978-3-030-63335-6_37

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