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Face recognition on 3D point clouds
Author(s): Ziyu Zhang; Feipeng Da; Chenxing Wang; Jian Yu; Yi Yu
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Paper Abstract

Point cloud has achieved great attention in 3D object classification, segmentation and indoor scene semantic parsing. In terms of face recognition, although image-based algorithm become more accurate and faster, open world face recognition still suffers from the influences i.e. illumination, occlusion, pose, etc. 3D face recognition based on point cloud containing both shape and texture information can compensate these shortcomings. However training a network to extract discriminative 3D feature is model complex and time inefficient due to the lack of large training dataset. To address these problems, we propose a novel 3D face recognition network(FPCNet) using modified PointNet++ and a 3D augmentation technique. Face-based loss and multi-label loss are used to train the FPCNet to enhance the learned features more discriminative. Moreover, a 3D face data augmentation method is proposed to synthesize more identity-variance and expression-variance 3D faces from limited data. Our proposed method shows excellent recognition results on CASIA-3D, Bosphorus and FRGC2.0 datasets and generalizes well for other datasets.

Paper Details

Date Published: 16 October 2019
PDF: 6 pages
Proc. SPIE 11205, Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019), 112051O (16 October 2019); doi: 10.1117/12.2541704
Show Author Affiliations
Ziyu Zhang, Southeast Univ. (China)
Shenzen Research Institute (China)
Feipeng Da, Southeast Univ. (China)
Shenzen Research Institute (China)
Chenxing Wang, Southeast Univ. (China)
Shenzen Research Institute (China)
Jian Yu, Southeast Univ. (China)
Shenzen Research Institute (China)
Yi Yu, Southeast Univ. (China)
Shenzen Research Institute (China)


Published in SPIE Proceedings Vol. 11205:
Seventh International Conference on Optical and Photonic Engineering (icOPEN 2019)
Anand Asundi; Motoharu Fujigaki; Huimin Xie; Qican Zhang; Song Zhang; Jianguo Zhu; Qian Kemao, Editor(s)

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