Thermal Non-Line-of-Sight Imaging

We propose a novel non-line-of-sight (NLOS) imaging framework with long-wave infrared (IR). At long-wave IR wavelengths, certain physical parameters are more favorable for high-fidelity reconstruction. In contrast to prior work in visible light NLOS, at long-wave IR wavelengths, the hidden heat sour...

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Bibliographic Details
Published inIEEE International Conference on Computational Photography pp. 1 - 11
Main Authors Maeda, Tomohiro, Yiqin Wang, Raskar, Ramesh, Kadambi, Achuta
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2019
Subjects
Cameras
computational photography
Image reconstruction
infrared imaging
non-line-of-sight imaging
Nonlinear optics
Pose estimation
Surface reconstruction
Two dimensional displays
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Summary:We propose a novel non-line-of-sight (NLOS) imaging framework with long-wave infrared (IR). At long-wave IR wavelengths, certain physical parameters are more favorable for high-fidelity reconstruction. In contrast to prior work in visible light NLOS, at long-wave IR wavelengths, the hidden heat source acts as a light source. This simplifies the problem to a single bounce problem. In addition, surface reflectance has a much stronger specular reflection in the long-wave IR spectrum than in the visible light spectrum. We reformulate a light transport model that leverages these favorable physical properties of long-wave IR. Specifically, we demonstrate 2D shape recovery and 3D localization of a hidden object. Furthermore, we demonstrate near real-time and robust NLOS pose estimation of a human figure, the first such demonstration, to our knowledge.
ISSN:2472-7636
DOI:10.1109/ICCPHOT.2019.8747343