scholarly journals AVATAR: AI Vision Analysis for Three-dimensional Action in Real-time

2022 ◽  
Author(s):  
Daesoo Kim ◽  
Dae-Gun Kim ◽  
Anna Shin ◽  
Yong-Cheol Jeong ◽  
Seahyung Park
Keyword(s):  
Artificial Intelligence ◽  
High Resolution ◽  
Real Time ◽  
Closed Loop ◽  
Three Dimensional ◽  
Body Parts ◽  
Behavioural Analysis ◽  
Action Sequences ◽  
Freely Moving ◽  
Behavioural Experiments

Artificial intelligence (AI) is an emerging tool for high-resolution behavioural analysis and conduction of human-free behavioural experiments. Here, we applied an AI-based system, AVATAR, which automatically virtualises 3D motions from the detection of 9 body parts. This allows quantification, classification and detection of specific action sequences in real-time and facilitates closed-loop manipulation, triggered by the onset of specific behaviours, in freely moving mice.

High-resolution Real-time Sonography: The Study of Superficial Body Parts

1984 ◽  
Vol 68 (6) ◽  
pp. 1609-1629
Author(s):  
Edward G. Grant ◽  
Jerry Earll ◽  
James D. Richardson ◽  
Anne Dunne
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Body Parts

Fast 3D image reconstruction algorithm based on artificial intelligence technology

2021 ◽  
pp. 002072092098504
Author(s):  
An Weigang ◽  
Pan Jinxiao
Keyword(s):  
Artificial Intelligence ◽  
High Resolution ◽  
Image Reconstruction ◽  
Three Dimensional ◽  
Feature Analysis ◽  
3D Image ◽  
3D Images ◽  
Dimensional Image ◽  
Fine Grained ◽  
3D Image Reconstruction

In order to improve the 3D reconstruction capability of high-resolution fine-grained 3D images, a fast 3D image reconstruction algorithm based on artificial intelligence technology is proposed. The cross-gradient sharpening detection method is used to collect features and extract information from high-resolution fine-grained three-dimensional images, and establish an edge contour feature detection model for high-resolution fine-grained three-dimensional images. Combining the salient feature analysis method and the subspace feature analysis method to cluster and analyze the high-resolution fine-grained three-dimensional image. In the artificial intelligence environment, the saliency of the three-dimensional image is detected and analyzed, and the multi-dimensional segmentation and gray histogram of the high-resolution fine-grained three-dimensional image are reconstructed through the subspace segmentation method. According to the reconstruction results of the gray histogram, fast 3D image reconstruction and image fusion processing are performed. Finally, the accurate detection and recognition of the reconstructed image is realized. The simulation results show that this method has a good effect on 3D image reconstruction, and the time cost of image reconstruction is relatively short. It improves the recognition and feature analysis capabilities of high-resolution fine-grained 3D images, and has good application value in the reconstruction, detection and recognition of high-resolution fine-grained 3D images.

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

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rachael Tobin ◽  
Abderrahim Halimi ◽  
Aongus McCarthy ◽  
Philip J. Soan ◽  
Gerald S. Buller
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Moving Objects ◽  
Single Photon ◽  
Three Dimensional ◽  
Depth Profiling ◽  
High Sensitivity ◽  
Single Photon Detection ◽  
Photon Detection ◽  
Uncertainty Estimates

AbstractRecently, 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.

scholarly journals Binary defocusing technique based on complementary decoding with unconstrained dual projectors

2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Xuexing Li ◽  
Wenhui Zhang
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Three Dimensional ◽  
Low Resolution ◽  
Fusion Technique ◽  
Space Time Coding ◽  
Depth Extraction ◽  
Core Idea ◽  
3D Scene ◽  
Binary Defocusing

AbstractBinary defocusing technique can effectively break the limitation of hardware speed, which has been widely used in the real-time three-dimensional (3D) reconstruction. In addition, fusion technique can reduce captured images count for a 3D scene, which helps to improve real-time performance. Unfortunately, it is difficult for binary defocusing technique and fusion technique working simultaneously. To this end, our research established a novel system framework consisting of dual projectors and a camera, where the position and posture of the dual projectors are not strictly required. And, the dual projectors can adjust defocusing level independently. Based on this, this paper proposed a complementary decoding method with unconstrained dual projectors. The core idea is that low-resolution information is employed for high-resolution phase unwrapping. For this purpose, we developed the low-resolution depth extraction strategy based on periodic space-time coding patterns and the method from the low-resolution order to high-resolution order of fringe. Finally, experimental results demonstrated the performance of our proposed method, and the proposed method only requires three images for a 3D scene, as well as has strong robustness, expansibility, and implementation.

scholarly journals A technique for obtaining 3D coordinates of human body parts from RGB-D stream

2018 ◽  
Vol 226 ◽  
pp. 05003
Author(s):  
Alexander V. Fisunov ◽  
Victoria B. Gnezdilova ◽  
Vladimir I. Marchuk
Keyword(s):  
Deep Learning ◽  
Real Time ◽  
Human Body ◽  
Three Dimensional ◽  
Depth Map ◽  
Body Parts ◽  
Combined Solution ◽  
Map Analysis

This paper proposes the method for real time determining three-dimensional coordinates of human body parts from RGB-D stream. Proposed method represent a combined solution in which deep learning and depth map analysis are used.

Understanding Interphase Boundary Dynamics by In Situ High-Resolution and Energy-Filtering Transmission Electron Microscopy and Real-Time Image Simulation

1998 ◽  
Vol 4 (3) ◽  
pp. 235-247 ◽  
Author(s):  
J.M. Howe ◽  
T.M. Murray ◽  
K.T. Moore ◽  
A.A. Csontos ◽  
M.M. Tsai ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Interphase Boundary ◽  
Three Dimensional ◽  
Atomic Level ◽  
Dimensional Structure ◽  
Energy Filtering ◽  
Transmission Electron ◽  
Boundary Dynamics

This study discusses the use of in situ high-resolution transmission electron microscropy (HRTEM) techniques to determine the structure, composition, and interphase boundary dynamics during phase transformations at the atomic level. Three main in situ HRTEM techniques are described: (1) in situ HRTEM dynamic studies that are performed on the same precipitate plates from different viewing directions to determine the three-dimensional structure of the interfaces; (2) in situ compositional mapping of precipitate interfaces obtained by energy-filtering TEM experiments at temperature in a HRTEM, and (3) real-time HRTEM image simulations that are being created for comparison with and interpretation of experimental in situ HRTEM dynamic observations. The results from these studies demonstrate that it is possible to understand the mechanisms and kinetics of interphase boundary motion at the atomic level.

scholarly journals Three-dimensional microscale hanging drop arrays with geometric control for drug screening and live tissue imaging

2021 ◽  
Vol 7 (17) ◽  
pp. eabc1323
Author(s):  
A. Ganguli ◽  
A. Mostafa ◽  
C. Saavedra ◽  
Y. Kim ◽  
P. Le ◽  
...  
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Drug Screening ◽  
Three Dimensional ◽  
3D Culture ◽  
Geometric Control ◽  
Hanging Drop ◽  
Design Elements ◽  
Trade Offs ◽  
On Chip

Existing three-dimensional (3D) culture techniques are limited by trade-offs between throughput, capacity for high-resolution imaging in living state, and geometric control. Here, we introduce a modular microscale hanging drop culture where simple design elements allow high replicates for drug screening, direct on-chip real-time or high-resolution confocal microscopy, and geometric control in 3D. Thousands of spheroids can be formed on our microchip in a single step and without any selective pressure from specific matrices. Microchip cultures from human LN229 glioblastoma and patient-derived mouse xenograft cells retained genomic alterations of originating tumors based on mate pair sequencing. We measured response to drugs over time with real-time microscopy on-chip. Last, by engineering droplets to form predetermined geometric shapes, we were able to manipulate the geometry of cultured cell masses. These outcomes can enable broad applications in advancing personalized medicine for cancer and drug discovery, tissue engineering, and stem cell research.

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