TY - GEN
T1 - Acoustic non-line-of-sight imaging
AU - Lindell, David B.
AU - Wetzstein, Gordon
AU - Koltun, Vladlen
N1 - KAUST Repository Item: Exported on 2022-06-30
Acknowledgements: This project was supported by a Terman Faculty Fellowship, a Sloan Fellowship, by the National Science Foundation (CAREER Award IIS 1553333), the DARPA REVEAL program, the ARO (Grant W911NF19-1-0120), and by the KAUST Office of Sponsored Research through the Visual Computing Center CCF grant. We also thank Ioannis Gkioulekas for an inspiring discussion.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2019/6
Y1 - 2019/6
N2 - Non-line-of-sight (NLOS) imaging enables unprecedented capabilities in a wide range of applications, including robotic and machine vision, remote sensing, autonomous vehicle navigation, and medical imaging. Recent approaches to solving this challenging problem employ optical time-of-flight imaging systems with highly sensitive time-resolved photodetectors and ultra-fast pulsed lasers. However, despite recent successes in NLOS imaging using these systems, widespread implementation and adoption of the technology remains a challenge because of the requirement for specialized, expensive hardware. We introduce acoustic NLOS imaging, which is orders of magnitude less expensive than most optical systems and captures hidden 3D geometry at longer ranges with shorter acquisition times compared to state-of-the-art optical methods. Inspired by hardware setups used in radar and algorithmic approaches to model and invert wave-based image formation models developed in the seismic imaging community, we demonstrate a new approach to seeing around corners.
AB - Non-line-of-sight (NLOS) imaging enables unprecedented capabilities in a wide range of applications, including robotic and machine vision, remote sensing, autonomous vehicle navigation, and medical imaging. Recent approaches to solving this challenging problem employ optical time-of-flight imaging systems with highly sensitive time-resolved photodetectors and ultra-fast pulsed lasers. However, despite recent successes in NLOS imaging using these systems, widespread implementation and adoption of the technology remains a challenge because of the requirement for specialized, expensive hardware. We introduce acoustic NLOS imaging, which is orders of magnitude less expensive than most optical systems and captures hidden 3D geometry at longer ranges with shorter acquisition times compared to state-of-the-art optical methods. Inspired by hardware setups used in radar and algorithmic approaches to model and invert wave-based image formation models developed in the seismic imaging community, we demonstrate a new approach to seeing around corners.
UR - http://hdl.handle.net/10754/679471
UR - https://ieeexplore.ieee.org/document/8953208/
UR - http://www.scopus.com/inward/record.url?scp=85077115518&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2019.00694
DO - 10.1109/CVPR.2019.00694
M3 - Conference contribution
SN - 9781728132938
SP - 6773
EP - 6782
BT - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
PB - IEEE
ER -