3D face landmarking with denoise auto-encoder networks

Liang Wang; Shaoyan Gai; Shuai Guo

doi:10.1117/12.2540978

14 August 2019 3D face landmarking with denoise auto-encoder networks

Liang Wang, Shaoyan Gai, Shuai Guo

Proceedings Volume 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019); 111793Q (2019) https://doi.org/10.1117/12.2540978
Event: Eleventh International Conference on Digital Image Processing (ICDIP 2019), 2019, Guangzhou, China

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.

Citation Download Citation

Liang Wang, Shaoyan Gai, and Shuai Guo "3D face landmarking with denoise auto-encoder networks", Proc. SPIE 11179, Eleventh International Conference on Digital Image Processing (ICDIP 2019), 111793Q (14 August 2019); https://doi.org/10.1117/12.2540978

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