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End-To-End Phase Retrieval from Single-Shot Fringe Image for 3D Face Reconstruction

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Image and Graphics (ICIG 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14357))

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Abstract

Phase retrieval is a critical aspect of structured light projection-based three-dimensional (3D) face imaging. The accurate extraction of desired phase information from a minimal number of fringe images without motion blur distortion remains a major challenge. Deep learning has gained attention in solving various optical measurement tasks, and in this study, we propose a deep learning-based dual-generator neural network (DGNET) that consists of two generators in series. The first generator filters interference caused by invalid regions, while the second converts valid regions in the fringe pattern into the final unwrapped phase. Moreover, the DGNET utilizes a single fringe image as input, which enhances the measurement speed and eliminates the impact of pose changes. Experimental results confirm the accuracy and feasibility of performing a phase-retrieval task from a single fringe pattern using the proposed DGNET.

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Acknowledgments

This research was funded by the Joint Funds of the National Natural Science Foundation of China under Grant -U1833128.

Author information

Authors and Affiliations

  1. National Key Laboratory of Fundamental Science on Synthetic Vision, Sichuan University, Chengdu, China

    Xiao Zhang, Zhi sheng You, Jiangping Zhu, Di You & Peng Cheng

  2. College of Computer Science, Sichuan University, Chengdu, China

    Jiangping Zhu

  3. School of Aeronautics and Astronautics, Sichuan University, Chengdu, China

    Peng Cheng

  4. Chengdu Aeronautic Polytechnic, Chengdu, China

    Xiao Zhang

Authors
  1. Xiao Zhang
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  2. Zhi sheng You
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  3. Jiangping Zhu
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  4. Di You
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  5. Peng Cheng
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Corresponding author

Correspondence to Peng Cheng .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Huchuan Lu

  2. University of Sydney, Sydney, NSW, Australia

    Wanli Ouyang

  3. Shenzhen University, Shenzhen, China

    Hui Huang

  4. Tsinghua University, Beijing, China

    Jiwen Lu

  5. Dalian University of Technology, Dalian, China

    Risheng Liu

  6. Institute of Automation, CAS, Beijing, China

    Jing Dong

  7. University of Technology Sydney, Sydney, NSW, Australia

    Min Xu

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Zhang, X., You, Z.s., Zhu, J., You, D., Cheng, P. (2023). End-To-End Phase Retrieval from Single-Shot Fringe Image for 3D Face Reconstruction. In: Lu, H., et al. Image and Graphics . ICIG 2023. Lecture Notes in Computer Science, vol 14357. Springer, Cham. https://doi.org/10.1007/978-3-031-46311-2_18

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  • DOI: https://doi.org/10.1007/978-3-031-46311-2_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-46310-5

  • Online ISBN: 978-3-031-46311-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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