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Perspective Phase Angle Model for Polarimetric 3D Reconstruction

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Computer Vision – ECCV 2022 (ECCV 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13662))

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Abstract

Current polarimetric 3D reconstruction methods, including those in the well-established shape from polarization literature, are all developed under the orthographic projection assumption. In the case of a large field of view, however, this assumption does not hold and may result in significant reconstruction errors in methods that make this assumption. To address this problem, we present the perspective phase angle (PPA) model that is applicable to perspective cameras. Compared with the orthographic model, the proposed PPA model accurately describes the relationship between polarization phase angle and surface normal under perspective projection. In addition, the PPA model makes it possible to estimate surface normals from only one single-view phase angle map and does not suffer from the so-called \(\pi \)-ambiguity problem. Experiments on real data show that the PPA model is more accurate for surface normal estimation with a perspective camera than the orthographic model.

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Acknowledgments

We thank the reviewers for their valuable feedback. This work was done while Guangcheng Chen was a visiting student at Southern University of Science and Technology. This work was supported in part by the National Natural Science Foundation of China under Grant No. 62173096, in part by the Leading Talents Program of Guangdong Province under Grant No. 2016LJ06G498 and 2019QN01X761, in part by Guangdong Province Special Fund for Modern Agricultural Industry Common Key Technology R &D Innovation Team under Grant No. 2019KJ129, in part by Guangdong Yangfan Program for Innovative and Entrepreneurial Teams under Grant No. 2017YT05G026.

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Authors and Affiliations

  1. Guangdong University of Technology, Guangzhou, China

    Guangcheng Chen & Yisheng Guan

  2. Southern University of Science and Technology, Shenzhen, China

    Guangcheng Chen, Li He & Hong Zhang

  3. Shenzhen Key Laboratory of Robotics and Computer Vision, Shenzhen, China

    Li He & Hong Zhang

Authors
  1. Guangcheng Chen
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  2. Li He
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  3. Yisheng Guan
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  4. Hong Zhang
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Corresponding author

Correspondence to Hong Zhang .

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Editors and Affiliations

  1. Tel Aviv University, Tel Aviv, Israel

    Shai Avidan

  2. University College London, London, UK

    Gabriel Brostow

  3. Google AI, Accra, Ghana

    Moustapha Cissé

  4. University of Catania, Catania, Italy

    Giovanni Maria Farinella

  5. Facebook (United States), Menlo Park, CA, USA

    Tal Hassner

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Chen, G., He, L., Guan, Y., Zhang, H. (2022). Perspective Phase Angle Model for Polarimetric 3D Reconstruction. In: Avidan, S., Brostow, G., Cissé, M., Farinella, G.M., Hassner, T. (eds) Computer Vision – ECCV 2022. ECCV 2022. Lecture Notes in Computer Science, vol 13662. Springer, Cham. https://doi.org/10.1007/978-3-031-20086-1_23

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  • DOI: https://doi.org/10.1007/978-3-031-20086-1_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20085-4

  • Online ISBN: 978-3-031-20086-1

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