Thermal Non-Line-of-Sight Imaging

Thermal Non-Line-of-Sight Imaging
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热非视距成像

DOI:
10.1109/iccphot.2019.8747343
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发表时间:
2019
期刊:
IEEE International Conference on Computational Photography
影响因子:
--
通讯作者:
Kadambi, Achuta
Kadambi, Achuta
中科院分区:
--
文献类型:
--
作者:
Maeda, Tomohiro;Wang, Yiqin;Raskar, Ramesh;Kadambi, Achuta

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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.
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