scholarly journals QUALIFICATION OF POINT CLOUDS MEASURED BY SFM SOFTWARE

2015 ◽  
Vol XL-4/W5 ◽  
pp. 125-130 ◽  
Author(s):  
K. Oda ◽  
S. Hattori ◽  
H. Saeki ◽  
T. Takayama ◽  
R. Honma
Keyword(s):  
Coordinate System ◽  
Structure From Motion ◽  
Point Cloud ◽  
Point Clouds ◽  
Sum Of Squares ◽  
Iterative Closest Point ◽  
Test Results ◽  
Reference Coordinate System ◽  
The Difference

This paper proposes a qualification method of a point cloud created by SfM (Structure-from-Motion) software. Recently, SfM software is popular for creating point clouds. Point clouds created by SfM Software seems to be correct, but in many cases, the result does not have correct scale, or does not have correct coordinates in reference coordinate system, and in these cases it is hard to evaluate the quality of the point clouds. To evaluate this correctness of the point clouds, we propose to use the difference between point clouds with different source of images. If the shape of the point clouds with different source of images is correct, two shapes of different source might be almost same. To compare the two or more shapes of point cloud, iterative-closest-point (ICP) is implemented. Transformation parameters (rotation and translation) are iteratively calculated so as to minimize sum of squares of distances. This paper describes the procedure of the evaluation and some test results.

scholarly journals OICP: An Online Fast Registration Algorithm Based on Rigid Translation Applied to Wire Arc Additive Manufacturing of Mold Repair

Materials ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1563
Author(s):  
Ruibing Wu ◽  
Ziping Yu ◽  
Donghong Ding ◽  
Qinghua Lu ◽  
Zengxi Pan ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Point Cloud ◽  
Point Clouds ◽  
Iterative Closest Point ◽  
Multiple Point ◽  
Icp Algorithm ◽  
Registration Algorithm ◽  
Cloud Models ◽  
Comparison Results ◽  
Wire Arc Additive Manufacturing

As promising technology with low requirements and high depositing efficiency, Wire Arc Additive Manufacturing (WAAM) can significantly reduce the repair cost and improve the formation quality of molds. To further improve the accuracy of WAAM in repairing molds, the point cloud model that expresses the spatial distribution and surface characteristics of the mold is proposed. Since the mold has a large size, it is necessary to be scanned multiple times, resulting in multiple point cloud models. The point cloud registration, such as the Iterative Closest Point (ICP) algorithm, then plays the role of merging multiple point cloud models to reconstruct a complete data model. However, using the ICP algorithm to merge large point clouds with a low-overlap area is inefficient, time-consuming, and unsatisfactory. Therefore, this paper provides the improved Offset Iterative Closest Point (OICP) algorithm, which is an online fast registration algorithm suitable for intelligent WAAM mold repair technology. The practicality and reliability of the algorithm are illustrated by the comparison results with the standard ICP algorithm and the three-coordinate measuring instrument in the Experimental Setup Section. The results are that the OICP algorithm is feasible for registrations with low overlap rates. For an overlap rate lower than 60% in our experiments, the traditional ICP algorithm failed, while the Root Mean Square (RMS) error reached 0.1 mm, and the rotation error was within 0.5 degrees, indicating the improvement of the proposed OICP algorithm.

scholarly journals ITERATIVE CLOSEST POINT ALGORITHM FOR ACCURATE REGISTRATION OF COARSELY REGISTERED POINT CLOUDS WITH CITYGML MODELS

2019 ◽  
Vol IV-2/W5 ◽  
pp. 201-208 ◽  
Author(s):  
S. Goebbels ◽  
R. Pohle-Fröhlich ◽  
P. Pricken
Keyword(s):  
Point Cloud ◽  
Point Clouds ◽  
Iteration Step ◽  
Iterative Closest Point ◽  
Target Point ◽  
Standard Tool ◽  
Iterative Closest Point Algorithm ◽  
Test Scenarios ◽  
Plane Mode ◽  
City Models

<p><strong>Abstract.</strong> The Iterative Closest Point algorithm (ICP) is a standard tool for registration of a source to a target point cloud. In this paper, ICP in point-to-plane mode is adopted to city models that are defined in CityGML. With this new point-to-model version of the algorithm, a coarsely registered photogrammetric point cloud can be matched with buildings’ polygons to provide, e.g., a basis for automated 3D facade modeling. In each iteration step, source points are projected to these polygons to find correspondences. Then an optimization problem is solved to find an affine transformation that maps source points to their correspondences as close as possible. Whereas standard ICP variants do not perform scaling, our algorithm is capable of isotropic scaling. This is necessary because photogrammetric point clouds obtained by the structure from motion algorithm typically are scaled randomly. Two test scenarios indicate that the presented algorithm is faster than ICP in point-to-plane mode on sampled city models.</p>

scholarly journals QUALITY PREDICTION OF DENSE POINTS GENERATED BY STRUCTURE FROM MOTION FOR HIGH-QUALITY AND EFFICIENT AS-IS MODEL RECONSTRUCTION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 95-101
Author(s):  
R. Moritani ◽  
S. Kanai ◽  
H. Date ◽  
Y. Niina ◽  
R. Honma
Keyword(s):  
Structure From Motion ◽  
Point Clouds ◽  
Quality Prediction ◽  
Construction Site ◽  
Model Reconstruction ◽  
High Quality ◽  
Bridge Column ◽  
Dense Point ◽  
Selection Of

<p><strong>Abstract.</strong> In this paper, we introduce a method for predicting the quality of dense points and selecting low-quality regions on the points generated by the structure from motion (SfM) and multi-view stereo (MVS) pipeline to realize high-quality and efficient as-is model reconstruction, using only results from the former: sparse point clouds and camera poses. The method was shown to estimate the quality of the final dense points as the quality predictor on an approximated model obtained from SfM only, without requiring the time-consuming MVS process. Moreover, the predictors can be used for selection of low-quality regions on the approximated model to estimate the next-best optimum camera poses which could improve quality. Furthermore, the method was applied to the prediction of dense point quality generated from the image sets of a concrete bridge column and construction site, and the prediction was validated in a time much shorter than using MVS. Finally, we discussed the correlation between the predictors and the final dense point quality.</p>

A New Kinect-Based Scanning System and its Application

2015 ◽  
Vol 764-765 ◽  
pp. 1375-1379 ◽  
Author(s):  
Cheng Tiao Hsieh
Keyword(s):  
Point Cloud ◽  
Depth Map ◽  
Bilateral Filter ◽  
Point Clouds ◽  
Digital Fabrication ◽  
Surface Model ◽  
Scanning System ◽  
3D Registration ◽  
Noise Point

This paper aims at presenting a simple approach utilizing a Kinect-based scanner to create models available for 3D printing or other digital manufacturing machines. The outputs of Kinect-based scanners are a depth map and they usually need complicated computational processes to prepare them ready for a digital fabrication. The necessary processes include noise filtering, point cloud alignment and surface reconstruction. Each process may require several functions and algorithms to accomplish these specific tasks. For instance, the Iterative Closest Point (ICP) is frequently used in a 3D registration and the bilateral filter is often used in a noise point filtering process. This paper attempts to develop a simple Kinect-based scanner and its specific modeling approach without involving the above complicated processes.The developed scanner consists of an ASUS’s Xtion Pro and rotation table. A set of organized point cloud can be generated by the scanner. Those organized point clouds can be aligned precisely by a simple transformation matrix instead of the ICP. The surface quality of raw point clouds captured by Kinect are usually rough. For this drawback, this paper introduces a solution to obtain a smooth surface model. Inaddition, those processes have been efficiently developed by free open libraries, VTK, Point Cloud Library and OpenNI.

scholarly journals body2vec: 3D Point Cloud Reconstruction for Precise Anthropometry with Handheld Devices

2020 ◽  
Vol 6 (9) ◽  
pp. 94
Author(s):  
Magda Alexandra Trujillo-Jiménez ◽  
Pablo Navarro ◽  
Bruno Pazos ◽  
Leonardo Morales ◽  
Virginia Ramallo ◽  
...  
Keyword(s):  
Network Architecture ◽  
Point Cloud ◽  
Point Clouds ◽  
Noise Removal ◽  
Extraction Methods ◽  
Anthropometric Measurements ◽  
Handheld Devices ◽  
Background Removal ◽  
3D Point Cloud Reconstruction

Current point cloud extraction methods based on photogrammetry generate large amounts of spurious detections that hamper useful 3D mesh reconstructions or, even worse, the possibility of adequate measurements. Moreover, noise removal methods for point clouds are complex, slow and incapable to cope with semantic noise. In this work, we present body2vec, a model-based body segmentation tool that uses a specifically trained Neural Network architecture. Body2vec is capable to perform human body point cloud reconstruction from videos taken on hand-held devices (smartphones or tablets), achieving high quality anthropometric measurements. The main contribution of the proposed workflow is to perform a background removal step, thus avoiding the spurious points generation that is usual in photogrammetric reconstruction. A group of 60 persons were taped with a smartphone, and the corresponding point clouds were obtained automatically with standard photogrammetric methods. We used as a 3D silver standard the clean meshes obtained at the same time with LiDAR sensors post-processed and noise-filtered by expert anthropological biologists. Finally, we used as gold standard anthropometric measurements of the waist and hip of the same people, taken by expert anthropometrists. Applying our method to the raw videos significantly enhanced the quality of the results of the point cloud as compared with the LiDAR-based mesh, and of the anthropometric measurements as compared with the actual hip and waist perimeter measured by the anthropometrists. In both contexts, the resulting quality of body2vec is equivalent to the LiDAR reconstruction.

scholarly journals Iterative K-Closest Point Algorithms for Colored Point Cloud Registration

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5331
Author(s):  
Ouk Choi ◽  
Min-Gyu Park ◽  
Youngbae Hwang
Keyword(s):  
Real World ◽  
Point Cloud ◽  
Point Clouds ◽  
The Other ◽  
Iterative Closest Point ◽  
Depth Images ◽  
The Cost ◽  
Soft Matching ◽  
Colored Point ◽  
Refinement Algorithm

We present two algorithms for aligning two colored point clouds. The two algorithms are designed to minimize a probabilistic cost based on the color-supported soft matching of points in a point cloud to their K-closest points in the other point cloud. The first algorithm, like prior iterative closest point algorithms, refines the pose parameters to minimize the cost. Assuming that the point clouds are obtained from RGB-depth images, our second algorithm regards the measured depth values as variables and minimizes the cost to obtain refined depth values. Experiments with our synthetic dataset show that our pose refinement algorithm gives better results compared to the existing algorithms. Our depth refinement algorithm is shown to achieve more accurate alignments from the outputs of the pose refinement step. Our algorithms are applied to a real-world dataset, providing accurate and visually improved results.

scholarly journals Construction and application of factory digital twin model based on BIM and point cloud

2021 ◽  
Vol 293 ◽  
pp. 02031
Author(s):  
Guocheng Qin ◽  
Ling Wang ◽  
YiMei Hou ◽  
HaoRan Gui ◽  
YingHao Jian
Keyword(s):  
Local Structure ◽  
Point Cloud ◽  
Point Clouds ◽  
Digital Factory ◽  
Digital Twin ◽  
Twin Model ◽  
Model Adjustment ◽  
Solid Foundation ◽  
Actual Location

The digital twin model of the factory is the basis for the construction of a digital factory, and the professional system of the factory is complex. The traditional BIM model is not completely consistent with the actual position of the corresponding component, and it is difficult to directly replace the digital twin model. In response to this situation, relying on a certain factory project, the point cloud is used to eliminate the positional deviation between the BIM model and the factory during the construction phase, improve the efficiency and accuracy and reliability of model adjustment and optimization, and , realize the conversion from BIM model to digital twin model. A novel algorithm is developed to quickly detect and evaluate the construction quality of the local structure of the factory, so as to input the initial deformation data of the structure into the corresponding model and feed back to the construction party for improvement. The results show that the digital twin model, which is highly consistent with the actual location of the factory components, not only lays a solid foundation for the construction of a digital factory, but also further deepens the integration and application of BIM and point clouds.

scholarly journals STUDI KUALITAS KIMIA DAN SENSORIK IKAN PINDANG BANDENG (Chanos chanos Forskal) TANPA DURI YANG DISIMPAN DALAM KEMASAN VAKUM SUHU AMBIENT

2020 ◽  
Vol 3 (2) ◽  
pp. 165
Author(s):  
Rahdi Fajar Miftahulkhair ◽  
Andi Besse Patadjai ◽  
Suwarjoyowirayatno Suwarjoyowirayatno
Keyword(s):  
Ambient Temperature ◽  
Storage Time ◽  
Vacuum Packaging ◽  
Test Results ◽  
Storage Duration ◽  
Chanos Chanos ◽  
Randomized Design ◽  
The Difference

ABSTRACT         The aim of this study was to determine the effect on the freshness quality of thorns leaves milkfish storing at ambient temperature in vacuum packaging. This study used a non-factorial randomized design (CRD) which was storage time consisting of 4 treatments H0 (0 days), H2 (2 days), H4 (4 days), and H6 (6 days). Each treatment was carried out with 3 times replication. Based on the test results, it showed that the difference in different storage duration significantly affected on freshness value of fish (TVB and TMA) of thorns leave milkfish at ambient temperature, along with the time of storage of vacuum packaged fish, the value of TVB and TMA increased on the 6th day of storage (H6) had the highest TVB and TMA values of 24.40 mgN / 100g and 3.43 mgN / 100g, respectively. Keywords: milkfish leave thorns, pindang, sensory, vacuum.ABSTRAKTujuan dari penelitian ini adalah untuk mengetahui nilai kesegaran ikan pindang bandeng tanpa duri kemasan vakum pada suhu ambient. Penelitian ini menggunakan rancangan percobaan adalah Rancangan Acak Lengkap (RAL) non faktorial yakni waktu penyimpanan yang terdiri dari 4 perlakuan yaitu H0 ( 0 hari), H2 (2 hari), H4 (4 hari) dan H6 (6 hari). Masing-masing perlakuan dilakukan sebanyak tiga kali pengulangan, sehingga diperoleh jumlah satuan percobaan sebanyak 12 unit. Berdasarkan hasil pengujian, perbedaan lama penyimpanan berbeda secara signifikan mempengaruhi nilai kesegaran ikan (TVB dan TMA) bandeng tanpa duri yang disimpan pada suhu ambeien, seiring dengan  waktu penyimpanan ikan pindang bandeng tanpa duri kemasan vakum, nilai TVB dan TMA meningkat. Pada hari ke 6 penyimpanan (H6) memiliki nilai TVB dan TMA tertinggi masing-masing 24,40 mgN/100g dan 3,43 mgN/100g.Kata kunci: ikan bandeng tanpa duri, pindang, vakum

scholarly journals TERRESTRIAL PHOTOGRAMMETRY VS LASER SCANNING FOR RAPID EARTHQUAKE DAMAGE ASSESSMENT

2018 ◽  
Vol XLII-3/W4 ◽  
pp. 527-533 ◽  
Author(s):  
C. Vasilakos ◽  
S. Chatzistamatis ◽  
O. Roussou ◽  
N. Soulakellis
Keyword(s):  
Structure From Motion ◽  
Damage Assessment ◽  
Point Cloud ◽  
Laser Scanning ◽  
Point Clouds ◽  
Earthquake Damage ◽  
Map Building ◽  
Dense Point ◽  
Terrestrial Photogrammetry ◽  
Earthquake Damage Assessment

<p><strong>Abstract.</strong> Building damage assessment caused by earthquakes is essential during the response phase following a catastrophic event. Modern techniques include terrestrial and aerial photogrammetry based on Structure from Motion algorithm and Laser Scanning with the latter to prove its superiority in accuracy assessment due to the high-density point clouds. However, standardized procedures during emergency surveys often could not be followed due to restrictions of outdoor operations because of debris or decrepit buildings, the high human presence of civil protection agencies, expedited deployment of survey team and cost of operations. The aim of this paper is to evaluate whether terrestrial photogrammetry based on a handheld amateur DSLR camera can be used to map building damages, structural deformations and facade production in an accepted accuracy comparing to laser scanning technique. The study area is the Vrisa village, Lesvos, Greece where a Mw&amp;thinsp;6.3 earthquake occurred on June 12th, 2017. A dense point cloud from some digital images created based on Structure from Motion algorithm and compared with a dense point cloud acquired by a laser scanner. The distance measurement and the comparison were conducted with the Multiscale Model to Model Cloud Comparison method. According to the results, the mean of the absolute distances between the two clouds is 0.038&amp;thinsp;m while the 94.9&amp;thinsp;% of the point distances are less than 0.1&amp;thinsp;m. Terrestrial photogrammetry proved to be an accurate methodology for rapid earthquake damage assessment thus its products were used by local authorities for the calculation of the compensation for the property loss.</p>

scholarly journals Experiment of Pullout Expansion Anchor in Installation Cast in Place and Post Installed with Concrete Breakout Failure

2021 ◽  
Vol 23 (1) ◽  
pp. 37-45
Author(s):  
Amirul Huda ◽  
Henry Apriyatno
Keyword(s):  
Pullout Test ◽  
Test Results ◽  
Pullout Capacity ◽  
Concrete Compressive Strength ◽  
Strength Tests ◽  
Effective Depth ◽  
The Difference ◽  
Better Than ◽  
Ready Mix Concrete

Abstract: The use of anchors in construction is gaining popularity to connect steel and concrete constructions, and to transmit tensile loads acting onto the concrete. This research aims to find out the difference in the strength of anchor based on two methods of installations that are cast in place compared to post installed with the influence of effective depth, diameter of anchor and quality of concrete, and failure of concrete breakout. Expansion anchor used in this study is "Sanko" M12x100 and ready-mix concrete PT Bonindo Ungaran, fc 25 MPa with 6 pieces of test specimens of 300x300x150 mm. Each specimen has 4 anchors with a distance between the anchors of 100 cm, the distance between the anchors to the edge of the concrete 100 mm, and the depth of installation (hef) of 60 mm. The result of the study is the predicted value of the anchor pullout capacity with the failure of concrete breakout due to the theoretical pullout, namely 42,223 N, anchor pullout test results with cast in place method of 40,574 N and post installed method by 37,494 N. Tensile strength tests (material) of anchor (fy) 338 MPa, for flat concrete compressive strength strength of (f’c) 25,698 MPa. The results of the cast in place pullout test are larger and better than post installed (40574 N>37494 N). Failure that occurred in cast in place method is a failure of concrete breakout and post installed method has occurred slip. Failures that occur are relevant to the theory.

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