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Proceedings Paper

3D face landmarking with denoise auto-encoder networks
Author(s): Liang Wang; Shaoyan Gai; Shuai Guo
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Paper Abstract

3D Facial landmarking plays an important role on 3D face recognition and face expression recognition. However, the most of methods underperform when faces have occluded region such as hair, glasses or finger. To solve this problem, a coarseto-fine method is proposed, containing several denoising auto-encoder networks (denoted as DANs). DANs not only can recover the lost information but improve the accuracy of landmarking. Tests based on Bosphorus dataset show a 100% of good landmarking under 6mm precision of mean error, which demonstrates that our algorithm achieves the state-of-theart performance.

Paper Details

Date Published: 14 August 2019
PDF: 6 pages
Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793Q (14 August 2019); doi: 10.1117/12.2540978
Show Author Affiliations
Liang Wang, Southeast Univ. (China)
Shaoyan Gai, Southeast Univ. (China)
Shuai Guo, Cardiff Univ. (United Kingdom)

Published in SPIE Proceedings Vol. 11179:
Eleventh International Conference on Digital Image Processing (ICDIP 2019)
Jenq-Neng Hwang; Xudong Jiang, Editor(s)

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