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.

@article{Heide:2019:NIW,
   author = "Felix Heide and Matthew O'Toole and Kai Zang and David Lindell and
      Steven Diamond and Gordon Wetzstein",
   title = "Non-line-of-sight Imaging with Partial Occluders and Surface Normals",
   journal = "ACM Transactions on Graphics",
   year = "2019",
   month = jun,
   volume = "38",
   number = "3",
   articleno = "22"
}