@article{ee4061df85ce48e7816ceeb83135fa01,
title = "Non-line-of-sight imaging with partial occluders and surface normals",
abstract = "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.",
keywords = "Computational photography, Non-line-of-sight imaging",
author = "Felix Heide and Matthew O'Toole and Kai Zang and Lindell, {David B.} and Steven Diamond and Gordon Wetzstein",
note = "Funding Information: The authors would like to thank James Harris for fruitful discussions. D.B.L. is supported by a Stanford Graduate Fellowship in Science and Engineering. G.W. is supported by a Terman Faculty Fellowship and a Sloan Fellowship. Additional funding was generously provided by the National Science Foundation (CAREER Award IIS 1553333), the DARPA REVEAL program, the ARO (Grant W911NF-19-1-0120), and by the KAUST Office of Sponsored Research through the Visual Computing Center CCF grant. Funding Information: Felix Heide now at Princeton. Matthew O{\textquoteright}Toole now at CMU D. B. L. is supported by a Stanford Graduate Fellowship in Science and Engineering. G. W. is supported by a Terman Faculty Fellowship and a Sloan Fellowship. Additional funding was generously provided by the National Science Foundation (CAREER Award IIS 1553333), the DARPA REVEAL program, the ARO (Grant W911NF-19-1-0120), and by the KAUST Office of Sponsored Research through the Visual Computing Center CCF grant. Authors{\textquoteright} addresses: F. Heide, 35 Olden Street, Princeton, NJ 08540-5233; email: fheide@cs.princeton.edu; M. O{\textquoteright}Toole, 4800 Forbes Ave., Pittsburgh, Pennsylvania 15213; email: mpotoole@cmu.edu; K. Zang, 1265 Lakeside Dr #3174 Sunnyvale, CA 94085; email: kai.zang@adaps-ph.com; D. Lindell, S. Diamond, and G. Wetzstein, 350 Serra Mall, Stanford, CA 94305; emails: {lindell, stevend2, gordon.wetzstein}@ stanford.edu. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org. {\textcopyright} 2019 Association for Computing Machinery. 0730-0301/2019/05-ART22 $15.00 https://doi.org/10.1145/3269977 Funding Information: D. B. L. is supported by a Stanford Graduate Fellowship in Science and Engineering. G. W. is supported by a Terman Faculty Fellowship and a Sloan Fellowship. Additional funding was generously provided by the National Science Foundation (CAREER Award IIS 1553333), the DARPA REVEAL program, the ARO (Grant W911NF-19-1-0120), and by the KAUST Office of Sponsored Research through the Visual Computing Center CCF grant. The authors would like to thank James Harris for fruitful discussions. D.B.L. is supported by a Stanford Graduate Fellowship in Science and Engineering. G.W. is supported by a Terman Faculty Fellowship and a Sloan Fellowship. Additional funding was generously provided by the National Science Foundation (CAREER Award IIS 1553333), the DARPA REVEAL program, the ARO (Grant W911NF-19-1-0120), and by the KAUST Office of Sponsored Research through the Visual Computing Center CCF grant. Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.",
year = "2019",
doi = "10.1145/3269977",
language = "English (US)",
volume = "38",
journal = "ACM Transactions on Computer Systems",
issn = "0730-0301",
publisher = "Association for Computing Machinery (ACM)",
number = "3",
}