scholarly journals SINGLE: Atomic-resolution structure identification of nanocrystals by graphene liquid cell EM

2021 ◽  
Vol 7 (5) ◽  
pp. eabe6679
Author(s):  
Cyril F. Reboul ◽  
Junyoung Heo ◽  
Chiara Machello ◽  
Simon Kiesewetter ◽  
Byung Hyo Kim ◽  
...  
Keyword(s):  
Electron Microscopy ◽  
3D Reconstruction ◽  
Three Dimensional ◽  
Atomic Resolution ◽  
Structure Identification ◽  
Reconstruction Method ◽  
Open Source Software Package ◽  
Liquid Cell ◽  
Phase Transmission ◽  
The Individual

Analysis of the three-dimensional (3D) structures of nanocrystals with solution-phase transmission electron microscopy is beginning to reveal their unique physiochemical properties. We developed a “one-particle Brownian 3D reconstruction method” based on imaging of ensembles of colloidal nanocrystals using graphene liquid cell electron microscopy. Projection images of differently rotated nanocrystals are acquired using a direct electron detector with high temporal (<2.5 ms) resolution and analyzed to obtain an ensemble of 3D reconstructions. Here, we introduce computational methods required for successful atomic-resolution 3D reconstruction: (i) tracking of the individual particles throughout the time series, (ii) subtraction of the interfering background of the graphene liquid cell, (iii) identification and rejection of low-quality images, and (iv) tailored strategies for 2D/3D alignment and averaging that differ from those used in biological cryo–electron microscopy. Our developments are made available through the open-source software package SINGLE.

A 3D Reconstruction Method Based on Binocular View Geometry

2010 ◽  
Vol 33 ◽  
pp. 299-303
Author(s):  
Zhong Yan Liu ◽  
Guo Quan Wang ◽  
Dong Ping Wang
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Feature Points ◽  
Imaging Model ◽  
Extrinsic Parameters ◽  
Image Acquisition System ◽  
Rearview Mirror ◽  
3D Information ◽  
Intrinsic And Extrinsic Parameters

A method was proposed to gain three-dimensional (3D) reconstruction based on binocular view geometry. Images used to calibrate cameras and reconstruct car’s rearview mirror by image acquisition system, by calibration image, a camera's intrinsic and extrinsic parameters, projective and fundamental matrixes were drawn by Matlab7.1;the collected rearview mirror images is pretreated to draw refined laser, extracted feature points, find the very appropriate match points by epipolar geometry principle; according to the camera imaging model to calculate the coordinates of space points, display point cloud, fitting space points to reconstruct car’s rearview mirror; experimental results show this method can better restore the car’s rearview mirror of 3D information.

Human Face Fast-3D-Reconstruction from a Single Image

2012 ◽  
Vol 157-158 ◽  
pp. 1008-1011
Author(s):  
Hui Huang Zhao ◽  
Yao Nan Wang ◽  
Ya Qi Sun ◽  
Jian Zhen Chen
Keyword(s):  
Wavelet Transform ◽  
3D Reconstruction ◽  
Wavelet Packet ◽  
Three Dimensional ◽  
Reconstruction Algorithm ◽  
Shape From Shading ◽  
Wavelet Packet Transform ◽  
Reconstruction Method ◽  
Human Face ◽  
Single Image

Human face three-dimensional (3D) reconstruction is a challenging problem. In this paper, we propose a human face fast- 3D- reconstruction method based on image processing with a single image. Shape from shading (SFS) is chosen to reconstruct the human face. First, SFS theory is introduced. It has the advantage of fast 3D reconstruction and only need a single image. Secondly, because the noise will affect the 3D reconstruction result greatly, wavelet transform and wavelet packet transform are introduced and used in image denoising respectively. The experiment has shown that the method based on wavelet transform produces the best denoising result than wavelet packet transform. At last, a human face 3D reconstruction algorithm based on a single image is proposed. The experimental results show that a human face 3D model can be reconstructed in fast by proposed algorithm.

A New Method for 3D Reconstruction of Headlight Contour

2013 ◽  
Vol 321-324 ◽  
pp. 862-867
Author(s):  
Fei Tao ◽  
Ping An Mu ◽  
Shu Guang Dai ◽  
Jia Xing Shen
Keyword(s):  
3D Reconstruction ◽  
Laser Scanning ◽  
Measurement Techniques ◽  
Three Dimensional ◽  
Contour Detection ◽  
Transformation Model ◽  
Laser Source ◽  
Reconstruction Method ◽  
Matching Effect ◽  
Geometry Model

This paper put forward a 3D reconstruction method of the headlight contours based on laser scanning technology and robotics. Firstly, according to the present three-dimensional measurement techniques, the article put forward a set of headlight contour detection method based on the analytic geometry model and the line laser source scanning principle. It establishes a 3D scanning model and coordinate transformation model for 3D reconstruction of the headlight contour. Secondly, according to the demanding accuracy it structures the 3D reconstruction system. Finally it realizes the 3D reconstruction of the headlight contour based on the method, and the result is tested and evaluated matching effect, the result shows that can effectively realize the 3D reconstruction of headlight contour and the method has a good stability.

scholarly journals Three-Dimensional Reconstruction-Based Vibration Measurement of Bridge Model Using UAVs

2021 ◽  
Vol 11 (11) ◽  
pp. 5111
Author(s):  
Zhihua Wu ◽  
Gongfa Chen ◽  
Qiong Ding ◽  
Bing Yuan ◽  
Xiaomei Yang
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Correction Method ◽  
Reference Points ◽  
Image Correlation ◽  
Vibration Measurement ◽  
Reconstruction Method ◽  
The Real ◽  
Bridge Model ◽  
Dimensional Reconstruction

This paper presents a measurement method of bridge vibration based on three-dimensional (3D) reconstruction. A video of bridge model vibration is recorded by an unmanned aerial vehicle (UAV), and the displacement of target points on the bridge model is tracked by the digital image correlation (DIC) method. Due to the UAV motion, the DIC-tracked displacement of the bridge model includes the absolute displacement caused by the excitation and the false displacement induced by the UAV motion. Therefore, the UAV motion must be corrected to measure the real displacement. Using four corner points on a fixed object plane as the reference points, the projection matrix for each frame of images can be estimated by the UAV camera calibration, and then the 3D world coordinates of the target points on the bridge model can be recovered. After that, the real displacement of the target points can be obtained. To verify the correctness of the results, the operational modal analysis (OMA) method is used to extract the natural frequencies of the bridge model. The results show that the first natural frequency obtained from the proposed method is consistent with the one obtained from the homography-based method. By further comparing with the homography-based correction method, it is found that the 3D reconstruction method can effectively overcome the limitation of the homography-based method that the fixed reference points and the target points must be coplanar.

scholarly journals Real-Time 3D Reconstruction Method Based on Monocular Vision

Sensors ◽  
2021 ◽  
Vol 21 (17) ◽  
pp. 5909
Author(s):  
Qingyu Jia ◽  
Liang Chang ◽  
Baohua Qiang ◽  
Shihao Zhang ◽  
Wu Xie ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Visual Information ◽  
Three Dimensional ◽  
Position Estimation ◽  
Monocular Vision ◽  
Cluster Center ◽  
Reconstruction Method ◽  
The Real ◽  
Depth Measurement

Real-time 3D reconstruction is one of the current popular research directions of computer vision, and it has become the core technology in the fields of virtual reality, industrialized automatic systems, and mobile robot path planning. Currently, there are three main problems in the real-time 3D reconstruction field. Firstly, it is expensive. It requires more varied sensors, so it is less convenient. Secondly, the reconstruction speed is slow, and the 3D model cannot be established accurately in real time. Thirdly, the reconstruction error is large, which cannot meet the requirements of scenes with accuracy. For this reason, we propose a real-time 3D reconstruction method based on monocular vision in this paper. Firstly, a single RGB-D camera is used to collect visual information in real time, and the YOLACT++ network is used to identify and segment the visual information to extract part of the important visual information. Secondly, we combine the three stages of depth recovery, depth optimization, and deep fusion to propose a three-dimensional position estimation method based on deep learning for joint coding of visual information. It can reduce the depth error caused by the depth measurement process, and the accurate 3D point values of the segmented image can be obtained directly. Finally, we propose a method based on the limited outlier adjustment of the cluster center distance to optimize the three-dimensional point values obtained above. It improves the real-time reconstruction accuracy and obtains the three-dimensional model of the object in real time. Experimental results show that this method only needs a single RGB-D camera, which is not only low cost and convenient to use, but also significantly improves the speed and accuracy of 3D reconstruction.

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