• Infrared and Laser Engineering
  • Vol. 49, Issue 6, 20200011 (2020)
Zhong Jinxin1、2, Yin Wei1、2, Feng Shijie1、2, Chen Qian2, and Zuo Chao1、2、*
Author Affiliations
  • 1[in Chinese]
  • 2[in Chinese]
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    DOI: 10.3788/irla20200011 Cite this Article
    Zhong Jinxin, Yin Wei, Feng Shijie, Chen Qian, Zuo Chao. Speckle projection profilometry with deep learning[J]. Infrared and Laser Engineering, 2020, 49(6): 20200011 Copy Citation Text show less
    References

    [1] X Su, Q Zhang. Dynamic 3-D shape measurement method: a review. Optics and Lasers in Engineering, 48, 191-204(2010).

    [2] S S Gorthi, P Rastogi. Fringe projection techniques: whither we are?. Optics and Lasers in Engineering, 48, 133-140(2010).

    [3] S Feng, L Zhang, C Zuo. High dynamic range 3d measurements with fringe projection profilometry: a review. Measurement Science and Technology, 29, 122001(2018).

    [4] S Zhang. High-speed 3D shape measurement with structured light methods: A review. Optics and Lasers in Engineering, 106, 119-131(2018).

    [5] P Zhou, J Zhu, H Jing. Optical 3-D surface reconstruction with color binary speckle pattern encoding. Optics Express, 26, 3452-3465(2018).

    [6] J Guo, X Peng, A Li. Automatic and rapid whole-body 3D shape measurement based on multinode 3D sensing and speckle projection. Applied Optics, 56, 8759-8768(2017).

    [7] B Pan, H Xie, Z Wang. Equivalence of digital image correlation criteria for pattern matching. Applied Optics, 49, 5501-5509(2010).

    [8] X Liu, H Zhao, G Zhan. Rapid and automatic 3D body measurement system based on a GPU-Steger line detector. Applied Optics, 55, 5539-5547(2016).

    [9] M Schaffer, M Grosse, B Harendt. High-speed three-dimensional shape measurements of objects with laser speckles and acousto-optical deflection. Optics Letters, 36, 3097-3099(2011).

    [10] G Lionello, L Cristofolini. A practical approach to optimizing the preparation of speckle patterns for digital-image correlation. Measurement Science and Technology, 25, 107001(2014).

    [11] F Zhong, R Kumar, C Quan. RGB laser speckles based 3D profilometry. Applied Physics Letters, 114, 201104(2019).

    [12] J García, Z Zalevsky, P García-Martínez. Three-dimensional mapping and range measurement by means of projected speckle patterns. Applied Optics, 47, 3032-3040(2008).

    [13] P Zhou, J Zhu, Z You. 3-D face registration solution with speckle encoding based spatial-temporal logical correlation algorithm. Optics Express, 27, 21004-21019(2019).

    [14] Y LeCun, Y Bengio, G Hinton. Deep learning. Nature, 521, 436-444(2015).

    [15] Rivenson Y, Zhang Y, Günaydın H, et al. Phase recovery holographic image reconstruction using deep learning in neural wks[J]. Light: Science & Applications, 2018, 7(2): 17141.

    [16] A Sinha, J Lee, S Li. Lensless computational imaging through deep learning. Optica, 4, 1117-1125(2017).

    [17] S Feng, Q Chen, G Gu. Fringe pattern analysis using deep learning. Advanced Photonics, 1, 025001(2019).

    [18] S Feng, C Zuo, W Yin. Micro deep learning profilometry for high-speed 3D surface imaging. Optics and Lasers in Engineering, 121, 416-427(2019).

    [19] C Zuo, S Feng, L Huang. Phase shifting algorithms for fringe projection profilometry: A review. Optics and Lasers in Engineering, 109, 23-59(2018).

    [20] Malacara D. Optical Shop Testing[M]. New Yk: John Wiley & Sons, 2007, 59.

    [21] C Zuo, L Huang, M Zhang. Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review. Optics and Lasers in Engineering, 85, 84-103(2016).

    [22] Yin W, Chen Q, Feng S, et al. Tempal phase unwrapping using deep learning[J]. arXiv preprint arXiv: 1903.09836, 2019.

    [23] Yin W, Zuo C, Feng S, et al. Highspeed 3D shape measurement with the multiview system using deep learning[C]SPIE, 2019, 11189: 111890B.

    [24] J Zbontar, Y LeCun, others. Stereo matching by training a convolutional neural network to compare image patches. Journal of Machine Learning Research, 17, 2(2016).

    [25] Luo W, Schwing A G, Urtasun R. Efficient deep learning f stereo matching[C]IEEE, 2016: 56955703.

    [26] H Hirschmuller. Stereo processing by semiglobal matching and mutual information. IEEE Transactions on Pattern Analysis and Machine Intelligence, 30, 328-341(2007).

    [27] M Zhang, Q Chen, T Tao. Robust and efficient multi-frequency temporal phase unwrapping: optimal fringe frequency and pattern sequence selection. Optics Express, 25, 20381-20400(2017).

    [28] B Pan. Digital image correlation for surface deformation measurement: historical developments, recent advances and future goals. Measurement Science and Technology, 29, 082001(2018).

    [29] Zhang L, Curless B, Seitz S M. Spacetime stereo: Shape recovery f dynamic scenes[C]IEEE, 2003, 2: II367.

    [30] S Feng, C Zuo, T Tao. Robust dynamic 3-D measurements with motion-compensated phase-shifting profilometry. Optics and Lasers in Engineering, 103, 127-138(2018).

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    Zhong Jinxin, Yin Wei, Feng Shijie, Chen Qian, Zuo Chao. Speckle projection profilometry with deep learning[J]. Infrared and Laser Engineering, 2020, 49(6): 20200011
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