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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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Fast Computational Periscopy in Challenging Ambient Light Conditions through Optimized Preconditioning
Non-line-of-sight (NLOS) imaging is a rapidly advancing technology that provides asymmetric vision: seeing without being seen. Though limited in accuracy, resolution, and depth recovery compared to active methods, the capabilities of passive methods are especially surprising because they typically use only a single, inexpensive digital camera. One of the largest challenges in passive NLOS imaging is ambient background light, which limits the dynamic range of the measurement while carrying no useful information about the hidden part of the scene. In this work we propose a new reconstruction approach that uses an optimized linear transformation to balance the rejection of uninformative light with the retention of informative light, resulting in fast (video-rate) reconstructions of hidden scenes from photographs of a blank wall under high ambient light conditions.
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- Award ID(s):
- 1955219
- PAR ID:
- 10267299
- Date Published:
- Journal Name:
- Proc. IEEE Int. Conf. Computational Photography
- Page Range / eLocation ID:
- 1 to 9
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1109/ICCP51581.2021.9466264
