IEEE Access (Jan 2020)

SIAT-3DFE: A High-Resolution 3D Facial Expression Dataset

  • Yuping Ye,
  • Zhan Song,
  • Junguang Guo,
  • Yu Qiao

DOI
https://doi.org/10.1109/ACCESS.2020.2979518
Journal volume & issue
Vol. 8
pp. 48205 – 48211

Abstract

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3D facial expression dataset plays an essential role in computer vision and computer graphics, especially to the data-driven machine learning algorithms like deep-learning etc. In contrast with traditional low-resolution and low-accuracy 3D face related datasets, an accurate and dense facial expression database was introduced in this paper. During the period from January to June 2019, we have collected 8,000 3D facial expression models and 32,000 texture images from 500 subjects. The 3D facial capture device works based on structured light principle. The procedure of 3D face capture and property of 3D samples are introduced in details. The proposed high-accuracy 3D face dataset can be used in many 3D applications, like recognition, animation, and 3D facial expression simulations.

Keywords