Generalization of pixel-wise phase estimation by CNN and improvement of phase-unwrapping by MRF optimization for one-shot 3D scan

Description

Active stereo technique using single pattern projection, a.k.a. one-shot 3D scan, have drawn a wide attention from industry, medical purposes, etc. One severe drawback of one-shot 3D scan is sparse reconstruction. In addition, since spatial pattern becomes complicated for the purpose of efficient embedding, it is easily affected by noise, which results in unstable decoding. To solve the problems, we propose a pixel-wise interpolation technique for one-shot scan, which is applicable to any types of static pattern if the pattern is regular and periodic. This is achieved by U-net which is pretrained by CG with efficient data augmentation algorithm. In the paper, to further overcome the decoding instability, we propose a robust correspondence finding algorithm based on Markov random field (MRF) optimization. We also propose a shape refinement algorithm based on b-spline and Gaussian kernel interpolation using explicitly detected laser curves. Experiments are conducted to show the effectiveness of the proposed method using real data with strong noises and textures.

Journal

  • IEICE Proceeding Series

    IEICE Proceeding Series 78 P2-19-, 2023-07-23

    The Institute of Electronics, Information and Communication Engineers

Details 詳細情報について

  • CRID
    1390861317116359040
  • DOI
    10.34385/proc.78.p2-19
  • ISSN
    21885079
  • Text Lang
    en
  • Data Source
    • JaLC
  • Abstract License Flag
    Disallowed

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