Analysis of the three-dimensional lymphatic architecture of the periodontal tissue using a new 3D reconstruction method

2002 ◽  
Vol 56 (1) ◽  
pp. 60-65 ◽  
Author(s):  
Akira Fujimura ◽  
Yohichiro Nozaka
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Periodontal Tissue

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.

scholarly journals AN AUTOMATIC 3D RECONSTRUCTION METHOD BASED ON MULTI-VIEW STEREO VISION FOR THE MOGAO GROTTOES

2015 ◽  
Vol XL-4/W5 ◽  
pp. 171-176 ◽  
Author(s):  
J. Xiong ◽  
S. Zhong ◽  
L. Zheng
Keyword(s):  
3D Reconstruction ◽  
Stereo Vision ◽  
Measurement System ◽  
Stereo Matching ◽  
Three Dimensional ◽  
Texture Mapping ◽  
Reconstruction Method ◽  
Epipolar Constraint ◽  
Mogao Grottoes ◽  
Binocular Stereo

This paper presents an automatic three-dimensional reconstruction method based on multi-view stereo vision for the Mogao Grottoes. 3D digitization technique has been used in cultural heritage conservation and replication over the past decade, especially the methods based on binocular stereo vision. However, mismatched points are inevitable in traditional binocular stereo matching due to repeatable or similar features of binocular images. In order to reduce the probability of mismatching greatly and improve the measure precision, a portable four-camera photographic measurement system is used for 3D modelling of a scene. Four cameras of the measurement system form six binocular systems with baselines of different lengths to add extra matching constraints and offer multiple measurements. Matching error based on epipolar constraint is introduced to remove the mismatched points. Finally, an accurate point cloud can be generated by multi-images matching and sub-pixel interpolation. Delaunay triangulation and texture mapping are performed to obtain the 3D model of a scene. The method has been tested on 3D reconstruction several scenes of the Mogao Grottoes and good results verify the effectiveness of the method.

scholarly journals Three-Dimensional Reconstruction Method of Rapeseed Plants in the Whole Growth Period Using RGB-D Camera

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4628
Author(s):  
Xiaowen Teng ◽  
Guangsheng Zhou ◽  
Yuxuan Wu ◽  
Chenglong Huang ◽  
Wanjing Dong ◽  
...  
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Three Dimensional ◽  
Point Clouds ◽  
Depth Image ◽  
Scanning System ◽  
Reconstruction Method ◽  
Three Dimensional Reconstruction ◽  
Hardware Cost ◽  
Dimensional Reconstruction

The three-dimensional reconstruction method using RGB-D camera has a good balance in hardware cost and point cloud quality. However, due to the limitation of inherent structure and imaging principle, the acquired point cloud has problems such as a lot of noise and difficult registration. This paper proposes a 3D reconstruction method using Azure Kinect to solve these inherent problems. Shoot color images, depth images and near-infrared images of the target from six perspectives by Azure Kinect sensor with black background. Multiply the binarization result of the 8-bit infrared image with the RGB-D image alignment result provided by Microsoft corporation, which can remove ghosting and most of the background noise. A neighborhood extreme filtering method is proposed to filter out the abrupt points in the depth image, by which the floating noise point and most of the outlier noise will be removed before generating the point cloud, and then using the pass-through filter eliminate rest of the outlier noise. An improved method based on the classic iterative closest point (ICP) algorithm is presented to merge multiple-views point clouds. By continuously reducing both the size of the down-sampling grid and the distance threshold between the corresponding points, the point clouds of each view are continuously registered three times, until get the integral color point cloud. Many experiments on rapeseed plants show that the success rate of cloud registration is 92.5% and the point cloud accuracy obtained by this method is 0.789 mm, the time consuming of a integral scanning is 302 seconds, and with a good color restoration. Compared with a laser scanner, the proposed method has considerable reconstruction accuracy and a significantly ahead of the reconstruction speed, but the hardware cost is much lower when building a automatic scanning system. This research shows a low-cost, high-precision 3D reconstruction technology, which has the potential to be widely used for non-destructive measurement of rapeseed and other crops phenotype.

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.

REAL-TIME THREE-DIMENSIONAL RECONSTRUCTION FOR VOLUME-BASED SURGERY SIMULATIONS

2008 ◽  
Vol 20 (04) ◽  
pp. 205-218 ◽  
Author(s):  
Jyh-Fa Lee ◽  
Ming-Shium Hsieh ◽  
Chih-Wei Kuo ◽  
Ming-Dar Tsai ◽  
Ming Ma
Keyword(s):  
3D Reconstruction ◽  
Real Time ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Three Dimensional Reconstruction ◽  
Visual Responses ◽  
Haptic Interactions ◽  
Tissue Surfaces ◽  
Dimensional Reconstruction ◽  
Time Critical

This paper describes a three-dimensional reconstruction method to provide real-time visual responses for volume (constituted by tomographic slices) based surgery simulations. The proposed system uses dynamical data structures to record tissue triangles obtained from 3D reconstruction computation. Each tissue triangle in the structures can be modified or every structure can be deleted or allocated independently. Moreover, triangle reconstruction is optimized by only deleting or adding vertices from manipulated voxels that are classified as erosion (in which the voxels are changed from tissue to null) or generation (the voxels are changed from null to tissue). Therefore, by manipulating these structures, 3D reconstruction can be locally implemented for only manipulated voxels to achieve the highest efficiency without reconstructing tissue surfaces in the whole volume as general methods do. Three surgery simulation examples demonstrate that the proposed method can provide time-critical visual responses even under other time-consuming computations such as volume manipulations and haptic interactions.

scholarly journals Research on Outdoor Garden Scene Reconstruction Based on PMVS Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wei He
Keyword(s):  
3D Reconstruction ◽  
Point Cloud ◽  
Feature Matching ◽  
Rapid Development ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Feature Points ◽  
Three Dimensional Reconstruction ◽  
Dimensional Reconstruction ◽  
Internet Of Things Technology

The three-dimensional reconstruction of outdoor landscape is of great significance for the construction of digital city. With the rapid development of big data and Internet of things technology, when using the traditional image-based 3D reconstruction method to restore the 3D information of objects in the image, there will be a large number of redundant points in the point cloud and the density of the point cloud is insufficient. Based on the analysis of the existing three-dimensional reconstruction technology, combined with the characteristics of outdoor garden scene, this paper gives the detection and extraction methods of relevant feature points and adopts feature matching and repairing the holes generated by point cloud meshing. By adopting the candidate strategy of feature points and adding the mesh subdivision processing method, an improved PMVS algorithm is proposed and the problem of sparse point cloud in 3D reconstruction is solved. Experimental results show that the proposed method not only effectively realizes the three-dimensional reconstruction of outdoor garden scene, but also improves the execution efficiency of the algorithm on the premise of ensuring the reconstruction effect.

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