• Journal of Computational Design and Engineering
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• v.3 no.2
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• pp.102-111
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• 2016

In this paper, we study the problem of computing smooth feature curves from CAD type point clouds models. The proposed method reconstructs feature curves from the intersections of developable strip pairs which approximate the regions along both sides of the features. The generation of developable surfaces is based on a linear approximation of the given point cloud through a variational shape approximation approach. A line segment sequencing algorithm is proposed for collecting feature line segments into different feature sequences as well as sequential groups of data points. A developable surface approximation procedure is employed to refine incident approximation planes of data points into developable strips. Some experimental results are included to demonstrate the performance of the proposed method.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.714-724
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• 2021

The point cloud content is immersive content recorded by acquiring points and colors corresponding to the real environment and objects having three-dimensional location information. When a point cloud content consisting of three-dimensional points having position and color information is enlarged and rendered, the gap between the points widens and an empty hole occurs. In this paper, we propose a method for improving the quality of point cloud contents through inverse transformation-based interpolation using depth information for holes by finding holes that occur due to the gap between points when expanding the point cloud. The points on the back are rendered between the holes created by the gap between the points, acting as a hindrance to applying the interpolation method. To solve this, remove the points corresponding to the back side of the point cloud. Next, a depth map at the point in time when an empty hole is generated is extracted. Finally, inverse transform is performed to extract pixels from the original data. As a result of rendering content by the proposed method, the rendering quality improved by 1.2 dB in terms of average PSNR compared to the conventional method of increasing the size to fill the blank area.

• Journal of the Korea Society for Simulation
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• v.32 no.3
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• pp.1-8
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• 2023

Modeling of artificial targets in Synthetic Aperture radar (SAR) mainly simulates radar signals reflected from the faces and edges of the 3D Computer Aided Design (CAD) model with a ray-tracing method, and modeling of the clutter on the Earth's surface uses a method of distinguishing types with similar distribution characteristics through statistical analysis of the SAR image itself. In this paper, man-made targets on the surface and background clutter on the terrain are integrated and made into a three-dimensional (3D) point cloud scatterer model, and SAR image were created through computational signal processing. The results of the SAR Stripmap image generation of the actual automobile based SAR radar system and the results analyzed using EM modeling or statistical distribution models are compared with this 3D point cloud scatterer model. The modeling target is selected as an bridge because it has the characteristic of having both water surface and ground terrain around the bridge and is also a target of great interest in both military and civilian use.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.1250-1251
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• 2022

Measuring management is an important part of preventing the collapse of retaining walls in advance by evaluating their stability with a variety of measuring instruments. The current work of measuring management requires considerable human and material resources since measurement companies need to install measuring instruments at various places on the retaining wall and visit the construction site to collect measurement data and evaluate the stability of the retaining wall. It was investigated that the applicability of the current work of measuring management is poor at small and medium-sized urban construction sites(excavation depth<10m) where measuring management is not essential. Therefore, the purpose of this study is to develop a laser sensor-based hardware to support the wall displacement measurements and their control software applicable to small and medium-sized urban construction sites. The 2D lidar sensor, which is more economical than a 3D laser scanner, is applied as element technology. Additionally, the hardware is mounted on the corner strut of the retaining wall, and it collects point cloud data of the retaining wall by rotating the 2D lidar sensor 360° through a servo motor. Point cloud data collected from the hardware can be transmitted through Wi-Fi to a displacement analysis device (notebook). The hardware control software is designed to control the 2D lidar sensor and servo motor in the displacement analysis device by remote access. The process of analyzing the displacement of a retaining wall using the developed hardware and software is as follows: the construction site manager uses the displacement analysis device to 1)collect the initial point cloud data, and after a certain period 2)comparative point cloud data is collected, and 3)the distance between the initial point and comparison point cloud data is calculated in order. As a result of performing an indoor experiment, the analyses show that a displacement of approximately 15 mm can be identified. In the future, the integrated system of the hardware designed here, and the displacement analysis software to be developed can be applied to small and medium-sized urban construction sites through several field experiments. Therefore, effective management of the displacement of the retaining wall is possible in comparison with the current measuring management work in terms of ease of installation, dismantlement, displacement measurement, and economic feasibility.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.12
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• pp.505-518
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• 2023

3D point cloud semantic segmentation is a computer vision task that involves dividing the point cloud into different objects and regions by predicting the class label of each point. Existing 3D semantic segmentation models have some limitations in performing sufficient fusion of multi-modal features while ensuring both characteristics of 2D visual features extracted from RGB images and 3D geometric features extracted from point cloud. Therefore, in this paper, we propose MMCA-Net, a novel 3D semantic segmentation model using 2D-3D multi-modal features. The proposed model effectively fuses two heterogeneous 2D visual features and 3D geometric features by using an intermediate fusion strategy and a multi-modal cross attention-based fusion operation. Also, the proposed model extracts context-rich 3D geometric features from input point cloud consisting of irregularly distributed points by adopting PTv2 as 3D geometric encoder. In this paper, we conducted both quantitative and qualitative experiments with the benchmark dataset, ScanNetv2 in order to analyze the performance of the proposed model. In terms of the metric mIoU, the proposed model showed a 9.2% performance improvement over the PTv2 model using only 3D geometric features, and a 12.12% performance improvement over the MVPNet model using 2D-3D multi-modal features. As a result, we proved the effectiveness and usefulness of the proposed model.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.3
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• pp.135-140
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• 2013

In this paper, we discussed about the volume monitoring system of a landfill facility. We proposed the waste volume calculation method using the point cloud of the surface of three dimensional object by measurement of the point cloud by the three dimensional scanner, which is based upon the robot technique. This computes not only the quantity of waste volume for continuos monitoring but also it helps not only to predict the evaluation factor of the usable age of a landfill. facility. Furthermore, the measuring system of waste volume was applied to the landfill facility in Ansung city.

• Journal of the Korea Computer Graphics Society
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• v.21 no.2
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• pp.1-10
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• 2015

In this paper, we propose an improved surface reconstruction method from an oriented point cloud. Our method is a classical least-square scheme, but is based on the 7-direction box-spline and the BCC (Body-Centered Cubic) lattice, which results in surfaces with superior quality and lower computational overhead, compared to other methods based on the B-splines on the Cartesian lattice. Specifically, when compared with two of the most popular techniques our method results in better surfaces but only takes ${\approx}53%$ computation time.

• Architectural research
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• v.21 no.4
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• pp.111-116
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• 2019

The premise of this research is the recent advancement of Building Information Modeling(BIM) Technology and Laser Scanning Technology(3D Scanning). The purpose of the paper is to amplify the potential offered by the combination of BIM and Point Cloud Data (PCD) for structural analysis. Today, enormous amounts of construction site data can be potentially categorized and quantified through BIM software. One of the extraordinary strengths of BIM software comes from its collaborative feature, which can combine different sources of data and knowledge. There are vastly different ways to obtain multiple construction site data, and 3D scanning is one of the effective ways to collect close-to-reality construction site data. The objective of this paper is to emphasize the prospects of pre-scanning and post-scanning automation algorithms. The research aims to stimulate the recent development of 3D scanning and BIM technology to develop Scan-to-BIM. The paper will review the current issues of Scan-to-BIM tasks to achieve As-Built BIM and suggest how it can be improved. This paper will propose a method of coordinating and utilizing PCD for construction and structural analysis during construction.

• Tunnel and Underground Space
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• v.21 no.6
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• pp.439-449
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• 2011

The characteristics of rock fractures for engineering rock classification are investigated by analyzing three dimensional point cloud generated from adjusted digital images of a tunnel face during construction and the tunnel is reinforced based on the supporting pattern suggested by the RMR and the Q system using parameters extracted from those images. As results, it is possible saving time required from face mapping to tunnel reinforcing work, enhancing safety during face mapping work in tunnels and reliability of both the mapping information and selecting supporting pattern by storing the files of digital images and related information which can be checked again, if necessary sometime in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.2
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• pp.179-186
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• 2004

This study describes that the method of precision measurement of vehicle shape and the method of measurement the deformation that it is occurred the reason of accident using industrial photogrammatry. The curved shape is measured using the projection target which is able to acquire the point cloud data. 3D coordinates of the target were able to acquire through object picturing and analysis of coordinates. The acquired point cloud data was done 3D modeling to form the surface with TIN. Also, It able to interpretate a deformation surveying accurately the occurred parts of deformation, then can furnish to the analysis of traffic accident the precise and effective data.