Single-photon three-dimensional imaging at up to 10 kilometers range

Ingle

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

2019

Single-photon avalanche diodes (SPADs) are becoming popular in time-of-flight depth-ranging due to their unique ability to capture individual photons with picosecond timing resolution. However, ambient light (e.g., sunlight) incident on a SPAD-based 3D camera leads to severe non-linear distortions (pileup) in the measured waveform, resulting in large depth errors. We propose asynchronous single-photon 3D imaging, a family of acquisition schemes to mitigate pileup during data acquisition itself. Asynchronous acquisition temporally misaligns SPAD measurement windows and the laser cycles through deterministically predefined or randomized offsets. Our key insight is that pileup distortions can be "averaged out" by choosing a sequence of offsets that span the entire depth range. We develop a generalized image formation model and perform theoretical analysis to explore the space of asynchronous acquisition schemes and design high-performance schemes. Our simulations and experiments demonstrate an improvement in depth accuracy of up to an order of magnitude as compared to the state-ofthe-art, across a wide range of imaging scenarios, including those with high ambient flux. * Equal contribution †

Section: Single-photon 3d Imaging Modelmentioning

confidence: 99%

Asynchronous Single-Photon 3D Imaging

Ingle

2019 IEEE/CVF International Conference on Computer Vision (ICCV)

2019

IEEE Trans. on Image Process.

“…Fast reconstruction of 3D scenes using single-photon light detection and ranging (Lidar) technology is an important challenge which is important in applications such as autonomous driving [1], environmental monitoring [2]- [4] and defence [5]. A growing number of 3D imaging modalities is becoming increasingly popular [6], and single-photon Lidar offers appealing advantages, including low-power, a capability for long-range imaging [7] or imaging in complex media such as fog/smoke [8] and underwater [9], [10] with excellent range resolution (of the order of millimetres [11]). Recently, several algorithms have also been proposed to analyse distributed objects [12]- [17], i.e., when multiple surfaces are visible within each pixel.…”

Section: Introductionmentioning

confidence: 99%

Fast Online 3D Reconstruction of Dynamic Scenes From Individual Single-Photon Detection Events

Altmann

McLaughlin

Davies

2020

In this paper, we present an algorithm for online 3D reconstruction of dynamic scenes using individual times of arrival (ToA) of photons recorded by single-photon detector arrays. One of the main challenges in 3D imaging using single-photon Lidar is the integration time required to build ToA histograms and reconstruct reliable 3D profiles in the presence of non-negligible ambient illumination. This long integration time also prevents the analysis of rapid dynamic scenes using existing techniques. We propose a new method which does not rely on the construction of ToA histograms but allows, for the first time, individual detection events to be processed online, in a parallel manner in different pixels, while accounting for the intrinsic spatiotemporal structure of dynamic scenes. Adopting a Bayesian approach, a Bayesian model is constructed to capture the dynamics of the 3D profile and an approximate inference scheme based on assumed density filtering is proposed, yielding a fast and robust reconstruction algorithm able to process efficiently thousands to millions of frames, as usually recorded using single-photon detectors. The performance of the proposed method, able to process hundreds of frames per second, is assessed using a series of experiments conducted with static and dynamic 3D scenes and the results obtained pave the way to a new family of real-time 3D reconstruction solutions.

“…Cost of TI acquisition can be reduced dramatically with homodyne time-of-flight sensors [14][15][16] , and the increasing availability of single-photon avalanche diode (SPAD) detectors and detector arrays with time-correlated single photon counting (TCSPC) modules has led to their use in TI-based NLOS imaging [4][5][6][7][8][9][10][11][12] . SPADs with TCSPC are common in many LIDAR applications and were recently used for very long-range three-dimensional imaging 17 and to capture photometric and geometric information from as few as one detected photon per pixel [18][19][20][21] . In addition to lowering the cost of NLOS imaging systems, SPAD-based systems have facilitated the extension of previous round-trip distances of around 1 m to a few meters for NLOS hidden-object estimation 5 and over 50 m for human localization at long range by coupling a telescope to a single-element SPAD 9 .…”

mentioning

confidence: 99%

Computational periscopy with an ordinary digital camera

Saunders

Murray-Bruce

Goyal

2019

Nature

175

Computational periscopy with an ordinary digital camera This work was made openly accessible by BU Faculty. Please share how this access benefits you. Your story matters.Computing the proportions of light arriving from different directions allows a diffusely reflecting surface to play the role of a mirror in a periscope. Such computational periscopy has previously depended on light travel distances being proportional to times of flight and thus has mostly been achieved with expensive, specialized ultrafast optical systems 1-12 . We introduce a 2D computational periscopy technique that requires only a single photograph captured with an ordinary digital camera. Our technique recovers the position of an opaque object and the scene behind (but not completely obscured by) the object, where both the object and scene are outside the line of sight of the camera, without requiring controlled or time-varying illumination. Non-line-of-sight imaging with only inexpensive, ubiquitous equipment may have considerable value in monitoring of hazardous environments, navigation, and detecting hidden adversaries.