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 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.

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.

Three-dimensional reconstruction of the 40S ribosomal subunit from rabbit reticulocytes

1987 ◽  
Vol 45 ◽  
pp. 936-937
Author(s):  
Neng-Yu Zhang ◽  
Terence Wagenknecht ◽  
Michael Radermacher ◽  
Tom Obrig ◽  
Joachim Frank
Keyword(s):  
Three Dimensional ◽  
Ribosomal Subunit ◽  
Uranyl Acetate ◽  
Reconstruction Method ◽  
Single Exposure ◽  
Electron Dose ◽  
Ribosomal Subunits ◽  
40S Ribosomal Subunit ◽  
Dimensional Reconstruction ◽  
Rabbit Reticulocytes

We have reconstructed the 40S ribosomal subunit at a resolution of 4 nm using the single-exposure pseudo-conical reconstruction method of Radermacher et al.Small (40S) ribosomal subunits were Isolated from rabbit reticulocytes, applied to grids and negatively stained (0.5% uranyl acetate) in a manner that “sandwiches” the specimen between two layers of carbon. Regions of the grid exhibiting uniform and thick staining were identified and photographed twice (magnification 49,000X). The first micrograph was always taken with the specimen tilted by 50° and the second was of the Identical area untilted (Fig. 1). For each of the micrographs the specimen was subjected to an electron dose of 2000-3000 el/nm2.Three hundred thirty particles appearing in the L view (defined in [4]) were selected from both tilted- and untilted-specimen micrographs. The untilted particles were aligned and their rotational alignment produced the azimuthal angles of the tilted particles in the conical tilt series.

Three-dimensional Reconstruction of Microscopic Image Based on Multi-ST Algorithm

2020 ◽  
Vol 64 (2) ◽  
pp. 20506-1-20506-7
Author(s):  
Min Zhu ◽  
Rongfu Zhang ◽  
Pei Ma ◽  
Xuedian Zhang ◽  
Qi Guo
Keyword(s):  
3D Reconstruction ◽  
Three Dimensional ◽  
Scale Model ◽  
Microscopic Image ◽  
Multi Scale ◽  
Gaussian Pyramid ◽  
Cost Aggregation ◽  
Dimensional Reconstruction ◽  
Image Pairs ◽  
Accurate Matching

Abstract Three-dimensional (3D) reconstruction is extensively used in microscopic applications. Reducing excessive error points and achieving accurate matching of weak texture regions have been the classical challenges for 3D microscopic vision. A Multi-ST algorithm was proposed to improve matching accuracy. The process is performed in two main stages: scaled microscopic images and regularized cost aggregation. First, microscopic image pairs with different scales were extracted according to the Gaussian pyramid criterion. Second, a novel cost aggregation approach based on the regularized multi-scale model was implemented into all scales to obtain the final cost. To evaluate the performances of the proposed Multi-ST algorithm and compare different algorithms, seven groups of images from the Middlebury dataset and four groups of experimental images obtained by a binocular microscopic system were analyzed. Disparity maps and reconstruction maps generated by the proposed approach contained more information and fewer outliers or artifacts. Furthermore, 3D reconstruction of the plug gauges using the Multi-ST algorithm showed that the error was less than 0.025 mm.

scholarly journals Online Measurement of Deposit Surface in Electron Beam Freeform Fabrication

Sensors ◽  
2019 ◽  
Vol 19 (18) ◽  
pp. 4001 ◽  
Author(s):  
Shuhe Chang ◽  
Haoyu Zhang ◽  
Haiying Xu ◽  
Xinghua Sang ◽  
Li Wang ◽  
...  
Keyword(s):  
Electron Beam ◽  
3D Reconstruction ◽  
Three Dimensional ◽  
Thermal Conditions ◽  
Online Measurement ◽  
Three Dimensional Reconstruction ◽  
Continuous Change ◽  
Position Information ◽  
Freeform Fabrication ◽  
Dimensional Reconstruction

In the process of electron beam freeform fabrication (EBF3), due to the continuous change of thermal conditions and variability in wire feeding in the deposition process, geometric deviations are generated in the deposition of each layer. In order to prevent the layer-by-layer accumulation of the deviation, it is necessary to perform online geometry measurement for each deposition layer, based on which the error compensation can be done for the previous deposition layer in the next deposition layer. However, the traditional three-dimensional reconstruction method that employs structured laser cannot meet the requirements of long-term stable operation in the manufacturing process of EBF3. Therefore, this paper proposes a method to measure the deposit surfaces based on the position information of electron beam speckle, in which an electron beam is used to bombard the surface of the deposit to generate the speckle. Based on the structured information of the electron beam in the vacuum chamber, the three-dimensional reconstruction of the surface of the deposited parts is realized without need of additional structured laser sensor. In order to improve the detection accuracy, the detection error is theoretically analyzed and compensated. The absolute error after compensation is smaller than 0.1 mm, and the precision can reach 0.1%, which satisfies the requirements of 3D reconstruction of the deposited parts. An online measurement system is built for the surface of deposited parts in the process of electron beam freeform fabrication, which realizes the online 3D reconstruction of the surface of the deposited layer. In addition, in order to improve the detection stability of the whole system, the image processing algorithm suitable for this scene is designed. The reliability and speed of the algorithm are improved by ROI extraction, threshold segmentation, and expansion corrosion. In addition, the speckle size information can also reflect the thermal conditions of the surface of the deposited parts. Hence, it can be used for online detection of defects such as infusion and voids.

scholarly journals Diagnostic Method of Maxillomandibular Relation of Edentulous Ridges. Application of the Three-dimensional Reconstruction Method.

1995 ◽  
Vol 39 (6) ◽  
pp. 995-1003 ◽  
Author(s):  
Naotsugu Kawahata ◽  
Hideki Ono ◽  
Akihiko Otsuka ◽  
Tomomi Fukunaga ◽  
Yuji Kamashita ◽  
...  
Keyword(s):  
Diagnostic Method ◽  
Three Dimensional ◽  
Reconstruction Method ◽  
Three Dimensional Reconstruction ◽  
Dimensional Reconstruction

scholarly journals THREE-DIMENSIONAL RECONSTRUCTION BASED ON IMPROVED MARCHING CUBES ALGORITHM

2020 ◽  
Vol 20 (09) ◽  
pp. 2040002
Author(s):  
MONAN WANG ◽  
HAIYANG LUO ◽  
QI CUI
Keyword(s):  
3D Reconstruction ◽  
Medical Image ◽  
Interpolation Method ◽  
Three Dimensional ◽  
Linear Interpolation ◽  
Selection Method ◽  
Marching Cubes ◽  
Dimensional Reconstruction ◽  
Message Mapping ◽  
Opening And Closing

Based on the standard Marching Cubes (MC) algorithm, this paper proposes an improved MC algorithm. First, the original 15 topological configurations in the MC algorithm are increased to 24, which effectively avoid the generation of voids phenomenon. To further improve the speed of three-dimensional (3D) reconstruction, in this paper, the midpoint selection method is used instead of the linear interpolation method, and the 24 configurations are divided into three types. Each class corresponds to a thread. The multi-thread parallel processing is used to improve the calculation speed. The critical region is used to realize multi-thread synchronization, and then we designed a protocol mapping table according to the idea of the message mapping table. The function pointer is triggered by macro. Processing function is called by function pointer and completes the encapsulation of the protocol mapping table, which maintains the opening and closing principle of the class and ensures the scalability of the class. Through the improved MC algorithm accuracy verification and reconstruction speed verification, it is concluded that the improved MC algorithm can make up for the voids problem. By comparing the calculation time under the two platforms of Windows and Linux, the reconstruction speed of the improved MC algorithm is approximately 30% faster than the standard MC algorithm and 40% faster than the Masala algorithm. Finally, the algorithm is applied to the medical image 3D reconstruction system, and the accuracy and applicability of the algorithm are demonstrated by two sets of examples.

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