scholarly journals Non-Line-of-Sight Three-Dimensional Imaging with a Single-Pixel Camera

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
G. Musarra ◽  
A. Lyons ◽  
E. Conca ◽  
Y. Altmann ◽  
F. Villa ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Line Of Sight ◽  
Three Dimensional Imaging ◽  
Single Pixel ◽  
Non Line Of Sight

scholarly journals A Statistical Channel Model for Stochastic Antenna Inclination Angles

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Gang Liu ◽  
Ming Zhang ◽  
Yaming Bo
Keyword(s):  
Indoor Environment ◽  
Channel Model ◽  
Three Dimensional ◽  
Statistical Characteristics ◽  
Line Of Sight ◽  
Static State ◽  
Inclination Angles ◽  
Short Time ◽  
Tracing Method ◽  
Non Line Of Sight

The actions of a person holding a mobile device are not a static state but can be considered as a stochastic process since users can change the way they hold the device very frequently in a short time. The change in antenna inclination angles with the random actions will result in varied received signal intensity. However, very few studies and conventional channel models have been performed to capture the features. In this paper, the relationships between the statistical characteristics of the electric field and the antenna inclination angles are investigated and modeled based on a three-dimensional (3D) fast ray-tracing method considering both the diffraction and reflections, and the radiation patterns of an antenna with arbitrary inclination angles are deducted and included in the method. Two different conditions of the line-of-sight (LOS) and non-line-of-sight (NLOS) in the indoor environment are discussed. Furthermore, based on the statistical analysis, a semiempirical probability density function of antenna inclination angles is presented. Finally, a novel statistical channel model for stochastic antenna inclination angles is proposed, and the ergodic channel capacity is analyzed.

scholarly journals Single-pixel three-dimensional imaging with time-based depth resolution

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Ming-Jie Sun ◽  
Matthew P. Edgar ◽  
Graham M. Gibson ◽  
Baoqing Sun ◽  
Neal Radwell ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Depth Resolution ◽  
Three Dimensional Imaging ◽  
Single Pixel

scholarly journals Ultrafast light field tomography for snapshot transient and non-line-of-sight imaging

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xiaohua Feng ◽  
Liang Gao
Keyword(s):  
Applied Sciences ◽  
Light Field ◽  
Moving Objects ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Line Of Sight ◽  
Temporal Dimension ◽  
Time Resolved ◽  
Imaging Strategy ◽  
Non Line Of Sight

AbstractCameras with extreme speeds are enabling technologies in both fundamental and applied sciences. However, existing ultrafast cameras are incapable of coping with extended three-dimensional scenes and fall short for non-line-of-sight imaging, which requires a long sequence of time-resolved two-dimensional data. Current non-line-of-sight imagers, therefore, need to perform extensive scanning in the spatial and/or temporal dimension, restricting their use in imaging only static or slowly moving objects. To address these long-standing challenges, we present here ultrafast light field tomography (LIFT), a transient imaging strategy that offers a temporal sequence of over 1000 and enables highly efficient light field acquisition, allowing snapshot acquisition of the complete four-dimensional space and time. With LIFT, we demonstrated three-dimensional imaging of light in flight phenomena with a <10 picoseconds resolution and non-line-of-sight imaging at a 30 Hz video-rate. Furthermore, we showed how LIFT can benefit from deep learning for an improved and accelerated image formation. LIFT may facilitate broad adoption of time-resolved methods in various disciplines.

Dense Parallax Image Acquisition using Single-Pixel Imaging for Three-Dimensional Imaging

2020 ◽  
Author(s):  
Tetsuhiko Muroi ◽  
Ren Usami ◽  
Teruyoshi Nobukawa ◽  
Masato Miura ◽  
Eriko Watanabe ◽  
...  
Keyword(s):  
Image Acquisition ◽  
Three Dimensional ◽  
Three Dimensional Imaging ◽  
Single Pixel

scholarly journals Non-line-of-sight imaging of moving objects obscured by a random corridor

2021 ◽  
Author(s):  
Tian Shi ◽  
Li Liangsheng ◽  
He Cai ◽  
Xianli Zhu ◽  
Qingfan Shi ◽  
...  
Keyword(s):  
Random Media ◽  
Moving Objects ◽  
Low Cost ◽  
Digital Camera ◽  
Line Of Sight ◽  
Intensity Correlation ◽  
Theoretical Limitation ◽  
Single Pixel ◽  
Corrected Intensity ◽  
Non Line Of Sight

Abstract Non-line-of-sight (NLOS) imaging makes it possible to reconstruct hidden objects around corners, which is of fundamental importance in various fields. Despite recent advances, NLOS imaging has not been studied in certain typical random scenarios, such as tortuous corridors filled with random media. We dub such a category of complex environment “random corridor”, and propose a reduced spatial- and ensemble-speckle intensity correlation (RSESIC) method to image a moving object obscured by a random corridor. Experimental results show that the method can reconstruct image of a centimeter-sized hidden object with a sub-millimeter resolution by a low-cost digital camera. The imaging capability depends on three system parameters and can be characterized by the correlation fidelity (CF). Furthermore, the RSESIC method is able to recover the image of objects even for a single pixel containing the contribution of about $10^2$ speckle grains, which overcomes the theoretical limitation of traditional speckle imaging methods. Last but not least, when the power attenuation of speckle intensity leads to the serious deterioration of CF, the image of hidden objects can still be reconstructed by the corrected intensity correlation.

Non-line-of-sight transparent object detection and reconstruction based on passive single-pixel imaging

2021 ◽  
Vol 18 (2) ◽  
pp. 025204
Author(s):  
Mengdi Li ◽  
Anumol Mathai ◽  
Xiping Xu ◽  
Xin Wang ◽  
Yue Pan ◽  
...  
Keyword(s):  
Object Detection ◽  
Line Of Sight ◽  
Transparent Object ◽  
Single Pixel ◽  
Non Line Of Sight
Sign in / Sign up

Export Citation Format

Share Document