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      Seeing around corners with edge-resolved transient imaging

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          Abstract

          Non-line-of-sight (NLOS) imaging is a rapidly growing field seeking to form images of objects outside the field of view, with potential applications in autonomous navigation, reconnaissance, and even medical imaging. The critical challenge of NLOS imaging is that diffuse reflections scatter light in all directions, resulting in weak signals and a loss of directional information. To address this problem, we propose a method for seeing around corners that derives angular resolution from vertical edges and longitudinal resolution from the temporal response to a pulsed light source. We introduce an acquisition strategy, scene response model, and reconstruction algorithm that enable the formation of 2.5-dimensional representations—a plan view plus heights—and a 180 field of view for large-scale scenes. Our experiments demonstrate accurate reconstructions of hidden rooms up to 3 meters in each dimension despite a small scan aperture (1.5-centimeter radius) and only 45 measurement locations.

          Abstract

          Non-line-of-sight imaging is typically limited by loss of directional information due to diffuse reflections scattering light in all directions. Here, the authors see around corners by using vertical edges and temporal response to pulsed light to obtain angular and longitudinal resolution, respectively.

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          Reversible jump Markov chain Monte Carlo computation and Bayesian model determination

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            Recovering three-dimensional shape around a corner using ultrafast time-of-flight imaging.

            The recovery of objects obscured by scattering is an important goal in imaging and has been approached by exploiting, for example, coherence properties, ballistic photons or penetrating wavelengths. Common methods use scattered light transmitted through an occluding material, although these fail if the occluder is opaque. Light is scattered not only by transmission through objects, but also by multiple reflection from diffuse surfaces in a scene. This reflected light contains information about the scene that becomes mixed by the diffuse reflections before reaching the image sensor. This mixing is difficult to decode using traditional cameras. Here we report the combination of a time-of-flight technique and computational reconstruction algorithms to untangle image information mixed by diffuse reflection. We demonstrate a three-dimensional range camera able to look around a corner using diffusely reflected light that achieves sub-millimetre depth precision and centimetre lateral precision over 40 cm×40 cm×40 cm of hidden space.
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              Confocal non-line-of-sight imaging based on the light-cone transform

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                Author and article information

                Contributors
                v.goyal@ieee.org
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                23 November 2020
                23 November 2020
                2020
                : 11
                : 5929
                Affiliations
                [1 ]GRID grid.189504.1, ISNI 0000 0004 1936 7558, Department of Electrical and Computer Engineering, , Boston University, ; 1 Silber Way, Boston, MA 02215 USA
                [2 ]GRID grid.417533.7, ISNI 0000 0004 0634 6125, Charles Stark Draper Laboratory, ; 555 Technology Square, Cambridge, MA 02139 USA
                [3 ]GRID grid.9531.e, ISNI 0000000106567444, School of Engineering and Physical Sciences, , Heriot-Watt University, ; Edinburgh, EH14 4AS UK
                [4 ]GRID grid.170693.a, ISNI 0000 0001 2353 285X, Department of Computer Science and Engineering, , University of South Florida, ; 4202 E. Fowler Avenue, Tampa, FL 33620 USA
                [5 ]GRID grid.508721.9, INP/ENSEEHIT-IRIT-TeSA, , University of Toulouse, ; Toulouse Cedex 7, Toulouse, 31071 France
                [6 ]GRID grid.116068.8, ISNI 0000 0001 2341 2786, Research Laboratory of Electronics, , Massachusetts Institute of Technology, ; 77 Massachusetts Avenue, Cambridge, MA 02139 USA
                Author information
                http://orcid.org/0000-0001-9171-1358
                http://orcid.org/0000-0003-3878-9142
                http://orcid.org/0000-0002-3177-9884
                http://orcid.org/0000-0002-9558-8294
                http://orcid.org/0000-0002-7381-7113
                http://orcid.org/0000-0001-8471-7049
                Article
                19727
                10.1038/s41467-020-19727-4
                7683558
                33230217
                3926ac1b-8bf8-42fd-a65c-7655a4528e70
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 February 2020
                : 23 October 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000185, United States Department of Defense | Defense Advanced Research Projects Agency (DARPA);
                Award ID: HR0011-16-C-0030
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100006353, Charles Stark Draper Laboratory (Draper Laboratory);
                Award ID: N00030-16-C-0014
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000001, National Science Foundation (NSF);
                Award ID: 1815896
                Award ID: 1955219
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000287, Royal Academy of Engineering;
                Award ID: RF201617/16/31
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000266, RCUK | Engineering and Physical Sciences Research Council (EPSRC);
                Award ID: EP/T00097X/1
                Award ID: EP/S000631/1
                Award Recipient :
                Funded by: MOD University Defence Research Collaboration (UDRC) in Signal Processing
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                Uncategorized
                imaging and sensing,imaging techniques
                Uncategorized
                imaging and sensing, imaging techniques

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