“Non-Line-of-Sight Imaging With Partial Occluders and Surface Normals” by Heide, O’Toole, Zang, Lindell, Diamond, et al. …

  • ©Felix Heide, Matthew O'Toole, Kai Zang, David B. Lindell, Steven Diamond, and Gordon Wetzstein




    Non-Line-of-Sight Imaging With Partial Occluders and Surface Normals


Session Title: Computational Imaging


    Imaging objects obscured by occluders is a significant challenge for many applications. A camera that could “see around corners” could help improve navigation and mapping capabilities of autonomous vehicles or make search and rescue missions more effective. Time-resolved single-photon imaging systems have recently been demonstrated to record optical information of a scene that can lead to an estimation of the shape and reflectance of objects hidden from the line of sight of a camera. However, existing non-line-of-sight (NLOS) reconstruction algorithms have been constrained in the types of light transport effects they model for the hidden scene parts. We introduce a factored NLOS light transport representation that accounts for partial occlusions and surface normals. Based on this model, we develop a factorization approach for inverse time-resolved light transport and demonstrate high-fidelity NLOS reconstructions for challenging scenes both in simulation and with an experimental NLOS imaging system.


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