Browse
Submit Data
Databases
API
Help

Dataset Information

27 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Robust real-time 3D imaging of moving scenes through atmospheric obscurant using single-photon LiDAR.

ABSTRACT: Recently, time-of-flight LiDAR using the single-photon detection approach has emerged as a potential solution for three-dimensional imaging in challenging measurement scenarios, such as over distances of many kilometres. The high sensitivity and picosecond timing resolution afforded by single-photon detection offers high-resolution depth profiling of remote, complex scenes while maintaining low power optical illumination. These properties are ideal for imaging in highly scattering environments such as through atmospheric obscurants, for example fog and smoke. In this paper we present the reconstruction of depth profiles of moving objects through high levels of obscurant equivalent to five attenuation lengths between transceiver and target at stand-off distances up to 150 m. We used a robust statistically based processing algorithm designed for the real time reconstruction of single-photon data obtained in the presence of atmospheric obscurant, including providing uncertainty estimates in the depth reconstruction. This demonstration of real-time 3D reconstruction of moving scenes points a way forward for high-resolution imaging from mobile platforms in degraded visual environments.

SUBMITTER: Tobin R

PROVIDER: S-EPMC8159934 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Real-time 3D reconstruction from single-photon lidar data using plug-and-play point cloud denoisers.

Project description:Single-photon lidar has emerged as a prime candidate technology for depth imaging through challenging environments. Until now, a major limitation has been the significant amount of time required for the analysis of the recorded data. Here we show a new computational framework for real-time three-dimensional (3D) scene reconstruction from single-photon data. By combining statistical models with highly scalable computational tools from the computer graphics community, we demonstrate 3D reconstruction of complex outdoor scenes with processing times of the order of 20?ms, where the lidar data was acquired in broad daylight from distances up to 320?metres. The proposed method can handle an unknown number of surfaces in each pixel, allowing for target detection and imaging through cluttered scenes. This enables robust, real-time target reconstruction of complex moving scenes, paving the way for single-photon lidar at video rates for practical 3D imaging applications.

| S-EPMC6825222 | biostudies-literature

Real-time 3D movement correction for two-photon imaging in behaving animals.

Project description:Two-photon microscopy is widely used to investigate brain function across multiple spatial scales. However, measurements of neural activity are compromised by brain movement in behaving animals. Brain motion-induced artifacts are typically corrected using post hoc processing of two-dimensional images, but this approach is slow and does not correct for axial movements. Moreover, the deleterious effects of brain movement on high-speed imaging of small regions of interest and photostimulation cannot be corrected post hoc. To address this problem, we combined random-access three-dimensional (3D) laser scanning using an acousto-optic lens and rapid closed-loop field programmable gate array processing to track 3D brain movement and correct motion artifacts in real time at up to 1 kHz. Our recordings from synapses, dendrites and large neuronal populations in behaving mice and zebrafish demonstrate real-time movement-corrected 3D two-photon imaging with submicrometer precision.

| S-EPMC7370269 | biostudies-literature

Robust Normal Estimation for 3D LiDAR Point Clouds in Urban Environments.

Project description:Normal estimation is a crucial first step for numerous light detection and ranging (LiDAR) data-processing algorithms, from building reconstruction, road extraction, and ground-cover classification to scene rendering. For LiDAR point clouds in urban environments, this paper presents a robust method to estimate normals by constructing an octree-based hierarchical representation for the data and detecting a group of large enough consistent neighborhoods at multiscales. Consistent neighborhoods are mainly determined based on the observation that an urban environment is typically comprised of regular objects, e.g., buildings, roads, and the ground surface, and irregular objects, e.g., trees and shrubs; the surfaces of most regular objects can be approximatively represented by a group of local planes. Even in the frequent presence of heavy noise and anisotropic point samplings in LiDAR data, our method is capable of estimating robust normals for kinds of objects in urban environments, and the estimated normals are beneficial to more accurately segment and identify the objects, as well as preserving their sharp features and complete outlines. The proposed method was experimentally validated both on synthetic and real urban LiDAR datasets, and was compared to state-of-the-art methods.

| S-EPMC6427512 | biostudies-other

MATRIEX imaging: multiarea two-photon real-time in vivo explorer.

Project description:Two-photon laser scanning microscopy has been extensively applied to study in vivo neuronal activity at cellular and subcellular resolutions in mammalian brains. However, the extent of such studies is typically confined to a single functional region of the brain. Here, we demonstrate a novel technique, termed the multiarea two-photon real-time in vivo explorer (MATRIEX), that allows the user to target multiple functional brain regions distributed within a zone of up to 12?mm in diameter, each with a field of view (FOV) of ~200??m in diameter, thus performing two-photon Ca2+ imaging with single-cell resolution in all of the regions simultaneously. For example, we demonstrate real-time functional imaging of single-neuron activities in the primary visual cortex, primary motor cortex and hippocampal CA1 region of mice in both anesthetized and awake states. A unique advantage of the MATRIEX technique is the configuration of multiple microscopic FOVs that are distributed in three-dimensional space over macroscopic distances (>1?mm) both laterally and axially but that are imaged by a single conventional laser scanning device. In particular, the MATRIEX technique can be effectively implemented as an add-on optical module for an existing conventional single-beam-scanning two-photon microscope without requiring any modification to the microscope itself. Thus, the MATRIEX technique can be readily applied to substantially facilitate the exploration of multiarea neuronal activity in vivo for studies of brain-wide neural circuit function with single-cell resolution.

| S-EPMC6881438 | biostudies-literature

Real-time multispectral fluorescence lifetime imaging using Single Photon Avalanche Diode arrays.

Project description:Autofluorescence spectroscopy has emerged in recent years as a powerful tool to report label-free contrast between normal and diseased tissues, both in vivo and ex vivo. We report the development of an instrument employing Single Photon Avalanche Diode (SPAD) arrays to realize real-time multispectral autofluorescence lifetime imaging at a macroscopic scale using handheld single-point fibre optic probes, under bright background conditions. At the detection end, the fluorescence signal is passed through a transmission grating and both spectral and temporal information are encoded in the SPAD array. This configuration allows interrogation in the spectral range of interest in real time. Spatial information is provided by an external camera together with a guiding beam that provides a visual reference that is tracked in real-time. Through fast image processing and data analysis, fluorescence lifetime maps are augmented on white light images to provide feedback of the measurements in real-time. We validate and demonstrate the practicality of this technique in the reference fluorophores and in articular cartilage samples mimicking the degradation that occurs in osteoarthritis. Our results demonstrate that SPADs together with fibre probes can offer means to report autofluorescence spectral and lifetime contrast in real-time and thus are suitable candidates for in situ tissue diagnostics.

| S-EPMC7229199 | biostudies-literature

Real-Time Queue Length Detection with Roadside LiDAR Data.

Project description:Real-time queue length information is an important input for many traffic applications. This paper presents a novel method for real-time queue length detection with roadside LiDAR data. Vehicles on the road were continuously tracked with the LiDAR data processing procedures (including background filtering, point clustering, object classification, lane identification and object association). A detailed method to identify the vehicle at the end of the queue considering the occlusion issue and package loss issue was documented in this study. The proposed method can provide real-time queue length information. The performance of the proposed queue length detection method was evaluated with the ground-truth data collected from three sites in Reno, Nevada. Results show the proposed method can achieve an average of 98% accuracy at the six investigated sites. The errors in the queue length detection were also diagnosed.

| S-EPMC7219237 | biostudies-literature

Real-Time Robust and Optimized Control of a 3D Overhead Crane System.

Project description:A new and advanced control system for three-dimensional (3D) overhead cranes is proposed in this study using state feedback control in discrete time to deliver high performance trajectory tracking with minimum load swings in high-speed motions. By adopting the independent joint control strategy, a new and simplified model is developed where the overhead crane actuators are used to design the controller, with all the nonlinear equations of motions being viewed as disturbances affecting each actuator. A feedforward control is then designed to tackle these disturbances via computed torque control technique. A new load swing control is designed along with a new motion planning scheme to robustly minimize load swings as well as allowing fast load transportation without violating system's constraints through updating reference trolley accelerations. The stability and performance analysis of the proposed discrete-time control system are demonstrated and validated analytically and practically.

| S-EPMC6696119 | biostudies-literature

Mid-infrared single-photon 3D imaging.

Project description:Active mid-infrared (MIR) imagers capable of retrieving three-dimensional (3D) structure and reflectivity information are highly attractive in a wide range of biomedical and industrial applications. However, infrared 3D imaging at low-light levels is still challenging due to the deficiency of sensitive and fast MIR sensors. Here we propose and implement a MIR time-of-flight imaging system that operates at single-photon sensitivity and femtosecond timing resolution. Specifically, back-scattered infrared photons from a scene are optically gated by delay-controlled ultrashort pump pulses through nonlinear frequency upconversion. The upconverted images with time stamps are then recorded by a silicon camera to facilitate the 3D reconstruction with high lateral and depth resolutions. Moreover, an effective numerical denoiser based on spatiotemporal correlation allows us to reveal the object profile and reflectivity under photon-starving conditions with a detected flux below 0.05 photons/pixel/second. The presented MIR 3D imager features high detection sensitivity, precise timing resolution, and wide-field operation, which may open new possibilities in life and material sciences.

| S-EPMC10256700 | biostudies-literature

Real-time 3D imaging of Haines jumps in porous media flow.

Project description:Newly developed high-speed, synchrotron-based X-ray computed microtomography enabled us to directly image pore-scale displacement events in porous rock in real time. Common approaches to modeling macroscopic fluid behavior are phenomenological, have many shortcomings, and lack consistent links to elementary pore-scale displacement processes, such as Haines jumps and snap-off. Unlike the common singular pore jump paradigm based on observations of restricted artificial capillaries, we found that Haines jumps typically cascade through 10-20 geometrically defined pores per event, accounting for 64% of the energy dissipation. Real-time imaging provided a more detailed fundamental understanding of the elementary processes in porous media, such as hysteresis, snap-off, and nonwetting phase entrapment, and it opens the way for a rigorous process for upscaling based on thermodynamic models.

| S-EPMC3593852 | biostudies-other

Sub-picosecond photon-efficient 3D imaging using single-photon sensors.

Project description:Active 3D imaging systems have broad applications across disciplines, including biological imaging, remote sensing and robotics. Applications in these domains require fast acquisition times, high timing accuracy, and high detection sensitivity. Single-photon avalanche diodes (SPADs) have emerged as one of the most promising detector technologies to achieve all of these requirements. However, these detectors are plagued by measurement distortions known as pileup, which fundamentally limit their precision. In this work, we develop a probabilistic image formation model that accurately models pileup. We devise inverse methods to efficiently and robustly estimate scene depth and reflectance from recorded photon counts using the proposed model along with statistical priors. With this algorithm, we not only demonstrate improvements to timing accuracy by more than an order of magnitude compared to the state-of-the-art, but our approach is also the first to facilitate sub-picosecond-accurate, photon-efficient 3D imaging in practical scenarios where widely-varying photon counts are observed.

| S-EPMC6286372 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data