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Non-line-of-sight snapshots and background mapping with an active corner camera

The ability to form reconstructions beyond line-of-sight view could be transformative in a variety of fields, including search and rescue, autonomous vehicle navigation, and reconnaissance. Most existing active non-line-of-sight (NLOS) imaging methods use data collection steps in which a pulsed lase...

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Autores principales: Seidel, Sheila, Rueda-Chacón, Hoover, Cusini, Iris, Villa, Federica, Zappa, Franco, Yu, Christopher, Goyal, Vivek K
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284852/
https://www.ncbi.nlm.nih.gov/pubmed/37344498
http://dx.doi.org/10.1038/s41467-023-39327-2
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author Seidel, Sheila
Rueda-Chacón, Hoover
Cusini, Iris
Villa, Federica
Zappa, Franco
Yu, Christopher
Goyal, Vivek K
author_facet Seidel, Sheila
Rueda-Chacón, Hoover
Cusini, Iris
Villa, Federica
Zappa, Franco
Yu, Christopher
Goyal, Vivek K
author_sort Seidel, Sheila
collection PubMed
description The ability to form reconstructions beyond line-of-sight view could be transformative in a variety of fields, including search and rescue, autonomous vehicle navigation, and reconnaissance. Most existing active non-line-of-sight (NLOS) imaging methods use data collection steps in which a pulsed laser is directed at several points on a relay surface, one at a time. The prevailing approaches include raster scanning of a rectangular grid on a vertical wall opposite the volume of interest to generate a collection of confocal measurements. These and a recent method that uses a horizontal relay surface are inherently limited by the need for laser scanning. Methods that avoid laser scanning to operate in a snapshot mode are limited to treating the hidden scene of interest as one or two point targets. In this work, based on more complete optical response modeling yet still without multiple illumination positions, we demonstrate accurate reconstructions of foreground objects while also introducing the capability of mapping the stationary scenery behind moving objects. The ability to count, localize, and characterize the sizes of hidden objects, combined with mapping of the stationary hidden scene, could greatly improve indoor situational awareness in a variety of applications.
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spelling pubmed-102848522023-06-23 Non-line-of-sight snapshots and background mapping with an active corner camera Seidel, Sheila Rueda-Chacón, Hoover Cusini, Iris Villa, Federica Zappa, Franco Yu, Christopher Goyal, Vivek K Nat Commun Article The ability to form reconstructions beyond line-of-sight view could be transformative in a variety of fields, including search and rescue, autonomous vehicle navigation, and reconnaissance. Most existing active non-line-of-sight (NLOS) imaging methods use data collection steps in which a pulsed laser is directed at several points on a relay surface, one at a time. The prevailing approaches include raster scanning of a rectangular grid on a vertical wall opposite the volume of interest to generate a collection of confocal measurements. These and a recent method that uses a horizontal relay surface are inherently limited by the need for laser scanning. Methods that avoid laser scanning to operate in a snapshot mode are limited to treating the hidden scene of interest as one or two point targets. In this work, based on more complete optical response modeling yet still without multiple illumination positions, we demonstrate accurate reconstructions of foreground objects while also introducing the capability of mapping the stationary scenery behind moving objects. The ability to count, localize, and characterize the sizes of hidden objects, combined with mapping of the stationary hidden scene, could greatly improve indoor situational awareness in a variety of applications. Nature Publishing Group UK 2023-06-21 /pmc/articles/PMC10284852/ /pubmed/37344498 http://dx.doi.org/10.1038/s41467-023-39327-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Seidel, Sheila
Rueda-Chacón, Hoover
Cusini, Iris
Villa, Federica
Zappa, Franco
Yu, Christopher
Goyal, Vivek K
Non-line-of-sight snapshots and background mapping with an active corner camera
title Non-line-of-sight snapshots and background mapping with an active corner camera
title_full Non-line-of-sight snapshots and background mapping with an active corner camera
title_fullStr Non-line-of-sight snapshots and background mapping with an active corner camera
title_full_unstemmed Non-line-of-sight snapshots and background mapping with an active corner camera
title_short Non-line-of-sight snapshots and background mapping with an active corner camera
title_sort non-line-of-sight snapshots and background mapping with an active corner camera
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10284852/
https://www.ncbi.nlm.nih.gov/pubmed/37344498
http://dx.doi.org/10.1038/s41467-023-39327-2
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