• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.93-103
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• 2023

The problem of reconstructing three-dimensional models of people and objects from color and depth images captured by low-cost RGB-D cameras has long been an active research area in computer graphics. Color and depth images captured by low-cost RGB-D cameras are represented as point clouds in three-dimensional space, which correspond to discrete values in a continuous three-dimensional space and require additional surface reconstruction compared to rendering using polygonal models. In this paper, we propose an effective ray-tracing based technique for visualizing point clouds rather than polygonal models. In particular, our method shows the possibility of an effective rendering method even in mobile environment which has limited performance due to processor heat and lack of battery.

• Journal of Cadastre & Land InformatiX
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• v.49 no.2
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• pp.57-66
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• 2019

Recently, as a part of the production of spatial information by smart cities, three-dimensional reproduction of structures for reverse engineering has been attracting attention. In particular, terrestrial LiDAR is mainly used for 3D reproduction of structures, and 3D reproduction research by UAS has been actively conducted. However, both technologies produce blind spots due to the shooting angle. This study deals with vertical structures. 3D model implemented through SfM-based image analysis technology using UAS and reproducibility and effectiveness of 3D models by terrestrial LiDAR-based laser scanning are examined. In addition, two 3D models are merged and reviewed to complement the blind spot. For this purpose, UAS based image is acquired for artificial rock wall, VCP and check point are set through GNSS equipment and total station, and 3D model of structure is reproduced by using SfM based image analysis technology. In addition, Through 3D LiDAR scanning, the 3D point cloud of the structure was acquired, and the accuracy of reproduction and completeness of the 3D model based on the checkpoint were compared and reviewed with the UAS-based image analysis results. In particular, accuracy and realistic reproducibility were verified through a combination of point cloud constructed from UAS and terrestrial LiDAR. The results show that UAS - based image analysis is superior in accuracy and 3D model completeness and It is confirmed that accuracy improves with the combination of two methods. As a result of this study, it is expected that UAS and terrestrial LiDAR laser scanning combination can complement and reproduce precise three-dimensional model of vertical structure, so it can be effectively used for spatial information construction, safety diagnosis and maintenance management.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.38-45
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• 2016

The objective of this research is to develop a method of improving MEP facility management based on 3D reverse engineering. Recently, 3D image scanning-based reverse engineering has been implemented in the fields of architecture, construction and (manufacturing). In the case where there are many objects and the MEP system is complicated, 3D reverse engineering is applied in semiconductor factories, because facility maintenance works cause the 2D drawing to be different from the original one. The 3D point cloud data obtained from 3D image scanning contains accurate data and can increase the efficiency of complicated MEP facility maintenance works. For this purpose, the present research studied the technology trends and analyzed the process of 3D reverse engineering. Based on the results, a method of improving MEP facility management is established and its effects described.

• Journal of the Korean Geophysical Society
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• v.9 no.4
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• pp.377-386
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• 2006

There is an inseparable relation between human race and engineering work. As world developed into highly industrialized society, a diversity of large structures is being built up correspondently to limited topographical circumstance. Though large structures are national establishments which provide us with convenience of life, there are some disastrous possibilities which were never predicted such as ground subsidence and degradation. It is very difficult to analyze the volume of total metamorphosis with the relative displacement measurement system which is now used and it is impossible to know whether there is structural metamorphosis within a permissible range of design or not. In this research with an object of 13-year-old earthen dam, through generating point-cloud which has 3D spatial coordinates(x, y, z) of this dam by means of 3D Laser Scanning, we can get real configuration data of slanting surface of this dam with this method of getting a number of 3D spatial coordinates(x, y, z). It gives 3D spatial model to us and we can get various information of this dam such as the distance of slanting surface of dam, dimensions and cubic volume. It can be made full use of as important source material of reinforcement and maintenance works to detect previously the bulging of the dam through this research.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.5
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• pp.436-443
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• 2011

Recognition of structures in urban environments is a fundamental ability for unmanned ground vehicles. In this paper we propose the geometrical featured voxel which has not only 3-D coordinates but also the type of geometrical properties of point cloud. Instead of dealing with a huge amount of point cloud collected by range sensors in urban, the proposed voxel can efficiently represent and save 3-D urban structures without loss of geometrical properties. We also provide an urban structure classification algorithm by using the proposed voxel and machine learning techniques. The proposed method enables to recognize urban environments around unmanned ground vehicles quickly. In order to evaluate an ability of the proposed map representation and the urban structure classification algorithm, our vehicle equipped with the sensor system collected range data and pose data in campus and experimental results have been shown in this paper.

• Journal of Korean Society of Rural Planning
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• v.27 no.4
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• pp.55-70
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• 2021

In this study, in the field of remote sensing, where the scope of application is rapidly expanding to fields such as land monitoring, disaster prediction, facility safety inspection, and maintenance of cultural properties, monitoring of rural space and surrounding environment using UAV is utilized. It was carried out to verify the possibility, and the following main results were derived. First, the aerial image taken with an unmanned aerial vehicle had a much higher image size and spatial resolution than the aerial image provided by the National Geographic Information Service. It was suitable for analysis due to its high accuracy. Second, the more the number of photographed photos and the more complex the terrain features, the more the point cloud included in the aerial image taken with the UAV was extracted. As the amount of point cloud increases, accurate 3D mapping is possible, For accurate 3D mapping, it is judged that a point cloud acquisition method for difficult-to-photograph parts in the air is required. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. Fourth, the digital elevation model(DEM) produced with aerial image taken with an UAV can visually express the altitude and shape of the topography of the study site, so it can be used as data to predict the effects of topographical changes due to changes in rural space. Therefore, it is possible to utilize various results using the data included in the aerial image taken by the UAV. In this study, the superiority of images acquired by UAV was verified by comparison with existing images, and the effect of 3D mapping on rural space monitoring was visually analyzed. If various types of spatial data such as GIS analysis and topographic map production are collected and utilized using data that can be acquired by unmanned aerial vehicles, it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

• The KIPS Transactions:PartB
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• v.16B no.1
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• pp.47-54
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• 2009

Automatic object recognition in 3D measuring data is of great interest in many application fields e.g. computer vision, reverse engineering and digital factory. In this paper we present a software tool for a fully automatic object detection and parameter estimation in unordered and noisy point clouds with a large number of data points. The software consists of three interactive modules each for model selection, point segmentation and model fitting, in which the orthogonal distance fitting (ODF) plays an important role. The ODF algorithms estimate model parameters by minimizing the square sum of the shortest distances between model feature and measurement points. The local quadric surface fitted through ODF to a randomly touched small initial patch of the point cloud provides the necessary initial information for the overall procedures of model selection, point segmentation and model fitting. The performance of the presented software tool will be demonstrated by applying to point clouds.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2004.10a
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• pp.201-206
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• 2004

Laser scanner are getting used for inspection and reverse engineering in industry such as motors, electronic products, dies and molds. However, due to the lack of efficient scanning technique, the tasks become limited to the low accuracy purpose. The main reasons for this limitation for usefulness are caused from the optical drawback, such as irregular reflection, scanning direction normal to measuring surface, the influence of surface integrity, and other optical disturbances. To overcome these drawback of laser scanner, this study propose the mechanism to reduce the optical trouble by using the 2 kinds of rotational movement axis and by composing the spherical coordinate to scanning the surface keeping normal direction consistently. So, it could be designed and interfaced the measuring device to realize that mechanism, and then it could acquisite the accurate 3D form cloud data. Also, these data are compared with the standard master ball and the data acquisited from the touch point sensor, to evaluate the accuracy and stability of measurement and to demonstrate the implementation of an dental tooth purpose system

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.