Non-line-of-sight imaging using phasor-field virtual wave optics

被引:0
|
作者
Xiaochun Liu
Ibón Guillén
Marco La Manna
Ji Hyun Nam
Syed Azer Reza
Toan Huu Le
Adrian Jarabo
Diego Gutierrez
Andreas Velten
机构
[1] University of Wisconsin Madison,Department of Electrical and Computer Engineering
[2] Universidad de Zaragoza—I3A,Graphics and Imaging Lab
[3] University of Wisconsin Madison,Department of Biostatistics and Medical Informatics
来源
Nature | 2019年 / 572卷
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Non-line-of-sight imaging allows objects to be observed when partially or fully occluded from direct view, by analysing indirect diffuse reflections off a secondary relay surface. Despite many potential applications1–9, existing methods lack practical usability because of limitations including the assumption of single scattering only, ideal diffuse reflectance and lack of occlusions within the hidden scene. By contrast, line-of-sight imaging systems do not impose any assumptions about the imaged scene, despite relying on the mathematically simple processes of linear diffractive wave propagation. Here we show that the problem of non-line-of-sight imaging can also be formulated as one of diffractive wave propagation, by introducing a virtual wave field that we term the phasor field. Non-line-of-sight scenes can be imaged from raw time-of-flight data by applying the mathematical operators that model wave propagation in a conventional line-of-sight imaging system. Our method yields a new class of imaging algorithms that mimic the capabilities of line-of-sight cameras. To demonstrate our technique, we derive three imaging algorithms, modelled after three different line-of-sight systems. These algorithms rely on solving a wave diffraction integral, namely the Rayleigh–Sommerfeld diffraction integral. Fast solutions to Rayleigh–Sommerfeld diffraction and its approximations are readily available, benefiting our method. We demonstrate non-line-of-sight imaging of complex scenes with strong multiple scattering and ambient light, arbitrary materials, large depth range and occlusions. Our method handles these challenging cases without explicitly inverting a light-transport model. We believe that our approach will help to unlock the potential of non-line-of-sight imaging and promote the development of relevant applications not restricted to laboratory conditions.
引用
收藏
页码:620 / 623
页数:3
相关论文
共 50 条
  • [41] Domain Reduction Strategy for Non-Line-of-Sight Imaging
    Shim, Hyunbo
    Cho, In
    Kwon, Daekyu
    Kim, Seon Joo
    COMPUTER VISION - ECCV 2024, PT XXXI, 2025, 15089 : 75 - 92
  • [42] Non-line-of-sight Imaging with Signal Superresolution Network
    Wang, Jianyu
    Liu, Xintong
    Xiao, Leping
    Shi, Zuoqiang
    Qiu, Lingyun
    Fu, Xing
    2023 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2023, : 17420 - 17429
  • [43] Compressive Non-Line-of-Sight Imaging with Deep Learning
    Zhu, Shenyu
    Sua, Yong Meng
    Bu, Ting
    Huang, Yu -Ping
    PHYSICAL REVIEW APPLIED, 2023, 19 (03)
  • [44] Exploiting Occlusion in Non-Line-of-Sight Active Imaging
    Thrampoulidis, Christos
    Shulkind, Gal
    Xu, Feihu
    Freeman, William T.
    Shapiro, Jeffrey H.
    Torralba, Antonio
    Wong, Franco N. C.
    Wornell, Gregory W.
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2018, 4 (03): : 419 - 431
  • [45] Calibration scheme for non-line-of-sight imaging setups
    Klein, Jonathan
    Laurenzis, Martin
    Hullin, Matthias B.
    Iseringhausen, Julian
    OPTICS EXPRESS, 2020, 28 (19): : 28324 - 28342
  • [46] Non-Line-of-Sight Imaging with Picosecond Temporal Resolution
    Wang, Bin
    Zheng, Ming-Yang
    Han, Jin-Jian
    Huang, Xin
    Xie, Xiu-Ping
    Xu, Feihu
    Zhang, Qiang
    Pan, Jian-Wei
    PHYSICAL REVIEW LETTERS, 2021, 127 (05)
  • [47] Non-line-of-sight imaging over 1.43 km
    Wu, Cheng
    Liu, Jianjiang
    Huang, Xin
    Li, Zheng-Ping
    Yu, Chao
    Ye, Jun-Tian
    Zhang, Jun
    Zhang, Qiang
    Dou, Xiankang
    Goyal, Vivek K.
    Xu, Feihu
    Pan, Jian-Wei
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2021, 118 (10)
  • [48] Photon-Efficient Non-Line-of-Sight Imaging
    Liu, Jianjiang
    Zhou, Yijun
    Huang, Xin
    Li, Zheng-Ping
    Xu, Feihu
    IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING, 2022, 8 : 639 - 650
  • [49] Steady-state Non-Line-of-Sight Imaging
    Chen, Wenzheng
    Daneau, Simon
    Mannan, Fahim
    Heide, Felix
    2019 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2019), 2019, : 3783 - 6792
  • [50] Non-line-of-sight imaging with adaptive artifact cancellation
    Zhou, Hongyuan
    Chen, Ziyang
    Qiu, Jumin
    Zhong, Sijia
    Zhang, Dejian
    Wang, Tongbiao
    Liu, Qiegen
    Yu, Tianbao
    OPTICS AND LASER TECHNOLOGY, 2025, 182