Exploiting Occlusion in Non-Line-of-Sight Active Imaging

Thrampoulidis, Christos; Shulkind, Gal; Xu, F.; Freeman, William T.; Shapiro, Jeffrey H.; Torralba, Antonio; Wong, Franco N. C.; Wornell, Gregory W.

doi:10.48550/arxiv.1711.06297

Cited by 4 publications

(14 citation statements)

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“…Certain other systems, intended for non-line-of-sight applications, rely on known structure in between the scene and the imaging plane to improve the conditioning of the problem [10], like windows [11] or corners of buildings [12]. These can be viewed as instances of broader class of coded-aperture systems that we analyze, in which the mask is naturally occurring and not chosen.…”

Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Aperture Design in Computational Imaging

Yedidia¹,

Thrampoulidis²,

Wornell³

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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There is growing interest in the use of coded aperture imaging systems for a variety of applications. Using an analysis framework based on mutual information, we examine the fundamental limits of such systems-and the associated optimum aperture coding-under simple but meaningful propagation and sensor models. Among other results, we show that when thermal noise dominates, spectrally-flat masks, which have 50% transmissivity, are optimal, but that when shot noise dominates, randomly generated masks with lower transmissivity offer greater performance. We also provide comparisons to classical pinhole cameras.Index Termscoded aperture cameras, computational photography, optical signal processing

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Section: Introductionmentioning

confidence: 99%

Analysis and Optimization of Aperture Design in Computational Imaging

Yedidia¹,

Thrampoulidis²,

Wornell³

2018

2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…In concurrent work, Thrampoulidis et al [2017] developed an alternative model that also includes partial occlusions for NLOS imaging. As opposed to our model, this work assumes that the shape of the NLOS scene, including occluders, is known and only surface albedos need to be recovered.…”

Section: Related Workmentioning

confidence: 99%

Non-line-of-sight Imaging with Partial Occluders and Surface Normals

et al. 2019

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Fig. 1. Non-line-of-sight (NLOS) imaging aims at recovering the shape and albedo of objects hidden from a camera or a light source. Using ultra-fast pulsed illumination and single photon detectors, the light transport in the scene is sampled for visible objects (left). The global illumination components of these time-resolved measurements (A,E) contain sufficient information to estimate the shape of hidden objects (B,C). Using a novel formulation for NLOS light transport that models partial occlusions of hidden objects (D) via visibility terms (F), we demonstrate higher-fidelity reconstructions (C) than previous approaches to NLOS imaging (B).Imaging objects obscured by occluders is a significant challenge for many applications. A camera that could "see around corners" could help improve navigation and mapping capabilities of autonomous vehicles or make search and rescue missions more effective. Time-resolved single-photon imaging systems have recently been demonstrated to record optical information of a scene that can lead to an estimation of the shape and reflectance of objects hidden from the line of sight of a camera. However, existing nonline-of-sight (NLOS) reconstruction algorithms have been constrained in the types of light transport effects they model for the hidden scene parts. We introduce a factored NLOS light transport representation that accounts for partial occlusions and surface normals. Based on this model, we develop a factorization approach for inverse time-resolved light transport and demonstrate high-fidelity NLOS reconstructions for challenging scenes both in simulation and with an experimental NLOS imaging system.

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“…Recently, in [20], we proposed a new NLoS imaging framework that opportunistically exploits the presence of opaque occluders in the light propagation path within the hidden space to distinguish light emanating from different parts of the hidden scene (Supplementary Movie S1). This framework was shown to recover spatial information otherwise destroyed by diffuse reflection, without reliance on ultrafast ToF measurements.…”

Section: Introductionmentioning

confidence: 99%

“…The approach is reminiscent of pin-speck (or anti-pinhole) imaging [21,22], in which an occluder in the scene serves as a defacto lens that facilitates imaging. The focus of [20] was a theoretical study of the framework. The model developed there assumes additive signal-independent Gaussian noise, hence the reconstruction algorithm and the preliminary experiment reported in [20] are tailored to a Gaussian-likelihood method.…”

Section: Introductionmentioning

confidence: 99%

“…The focus of [20] was a theoretical study of the framework. The model developed there assumes additive signal-independent Gaussian noise, hence the reconstruction algorithm and the preliminary experiment reported in [20] are tailored to a Gaussian-likelihood method. This Gaussian-noise assumption, however, does not adequately represent shot-noise-limited operation, which prevails in the low-photon-count regime.…”

Section: Introductionmentioning

confidence: 99%

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Revealing hidden scenes by photon-efficient occlusion-based opportunistic active imaging

Xu,

Shulkind,

Thrampoulidis

et al. 2018

Preprint

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The ability to see around corners, i.e., recover details of a hidden scene from its reflections in the surrounding environment, is of considerable interest in a wide range of applications. However, the diffuse nature of light reflected from typical surfaces leads to mixing of spatial information in the collected light, precluding useful scene reconstruction. Here, we employ a computational imaging technique that opportunistically exploits the presence of occluding objects, which obstruct probe-light propagation in the hidden scene, to undo the mixing and greatly improve scene recovery. Importantly, our technique obviates the need for the ultrafast time-of-flight measurements employed by most previous approaches to hidden-scene imaging. Moreover, it does so in a photon-efficient manner based on an accurate forward model and a computational algorithm that, together, respect the physics of three-bounce light propagation and single-photon detection. Using our methodology, we demonstrate reconstruction of hiddensurface reflectivity patterns in a meter-scale environment from non-time-resolved measurements. Ultimately, our technique represents an instance of a rich and promising new imaging modality with important potential implications for imaging science.

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Exploiting Occlusion in Non-Line-of-Sight Active Imaging

Cited by 4 publications

References 0 publications

Analysis and Optimization of Aperture Design in Computational Imaging

Analysis and Optimization of Aperture Design in Computational Imaging

Non-line-of-sight Imaging with Partial Occluders and Surface Normals

Revealing hidden scenes by photon-efficient occlusion-based opportunistic active imaging

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