• International conference on construction engineering and project management
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• 2015.10a
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• pp.641-642
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• 2015

Unlike for other building processes, BIM for earthwork does not need a large variety of 3D model shapes; however, it requires a 3D model that can efficiently reflect the changing features of the ground shape and provide soil type-dependent workload calculation and information on equipment for optimal management. Objects for earthwork have not yet been defined because the current BIM system does not provide them. The BIM technology commonly applied in the manufacturing center uses real-object data obtained through 3D scanning to generate 3D parametric solid models. 3D scanning, which is used when there are no existing 3D models, has the advantage of being able to rapidly generate parametric solid models. In this study, A method to generate 3D models for earthwork operations using reverse engineering is suggested. 3D scanning is used to create a point cloud of a construction site and the point cloud data are used to generate a surface model, which was then converted into a parametric model with 3D objects for earthwork

• International Journal of CAD/CAM
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• v.12 no.1
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• pp.9-19
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• 2012

Generation of optimum planar B-spline curve in terms of minimum deviation and required fairness to approximate a target shape defined by a strip-shaped unorganized 2D point cloud is studied. It is proposed to use the location of control points as variables within the geometric optimization framework of point distance minimization. An adaptive simulated annealing heuristic optimization algorithm is developed to iteratively update an initial approximate curve towards the target shape. The new implementation comprises an adaptive cooling procedure in which the temperature change is adaptively dependent on the objective function evolution. It is shown that the proposed method results in an improved convergence speed when compared to the standard simulated annealing method. A couple of examples are included to show the applicability of the proposed method in the surface model reconstruction directly from point cloud data.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.1
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• pp.83-94
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• 2015

Deduplication, which is a technique of eliminating redundant data by storing only a single copy of each data, provides clients and a cloud server with efficiency for managing stored data. Since the data is saved in untrusted public cloud server, however, both invasion of data privacy and data loss can be occurred. Over recent years, although many studies have been proposed secure deduplication schemes, there still remains both the security problems causing serious damages and inefficiency. In this paper, we propose secure and efficient client-side deduplication with Key-server based on Bellare et. al's scheme and challenge-response method. Furthermore, we point out potential risks of client-side deduplication and show that our scheme is secure against various attacks and provides high efficiency for uploading big size of data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.1283-1287
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• 2003

Reverse engineering technology refers to the process that creates a CAD model of an existing part using measuring devices. Recently, non-contact scanning devices have become more accurate and the speed of data acquisition has increased drastically. However, they generate thousands of points per second and various types of point data. Therefore. it becomes a important to handle the huge amount and various types of point data to generate a surface model efficiently. This paper proposes a new triangular mesh generation method using 3D grids. The geometric information of a part can be obtained from point cloud data by estimating normal values of the points. In our research, the non-uniform 3D grids are generated first for feature based data reduction based on the geometric information. Then, triangulation is performed with the reduced point data. The grid structure is efficiently used not only for neighbor point search that can speed up the mesh generation process but also for getting surface connectivity information to result in same topology surface with the point data. Through this integrated approach, it is possible to create surface models from scanned point data efficiently.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.849-858
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• 2019

Recent developments in computer graphics technology and image processing technology have increased interest in point cloud technology for inputting real space and object information as three-dimensional data. In particular, point cloud technology can accurately provide spatial information, and has attracted a great deal of interest in the field of autonomous vehicles and AR (Augmented Reality)/VR (Virtual Reality). However, in order to provide users with 3D point cloud contents that require more data than conventional 2D images, various technology developments are required. In order to solve these problems, an international standardization organization, MPEG(Moving Picture Experts Group), is in the process of discussing efficient compression and transmission schemes. In this paper, we provide a region division transfer method of 3D point cloud content through extension of existing MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-SRD (Spatial Relationship Description) technology, quality parameters are further defined in the signaling message so that the quality parameters can be selectively determined according to the user's request. We also design a verification platform for ROUTE (Real Time Object Delivery Over Unidirectional Transport)/DASH based heterogeneous network environment and use the results to validate the proposed technology.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of Digital Convergence
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• v.18 no.11
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• pp.427-432
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• 2020

In order to establish an effective forest management plan, it is necessary to investigate tree management information such as tree height and DBH(Diameter at breast height). However, research on convergence and application of data acquisition technology to improve the efficiency of existing forest survey methods is insufficient. Therefore, in this study, tree management information was constructed and analyzed using point cloud data acquired through a 3D scanner. Data on the study site was acquired using fixed and mobile 3D scanners, and the efficiency of the mobile 3D scanner was presented through comparison of working hours. In addition, tree management information for object management was constructed by classifying vegetation by object using point cloud data, and by constructing information on chest height diameter and height. As a result of the accuracy evaluation compared with the conventional measurement method, the difference in tree height was 0.02-0.09m and DBH was 0.01-0.04m. If information on the location of vegetation and crowns of each object is constructed through additional research in the future, the efficiency of the work related to forest management information construction can be greatly increased.

• 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.

• Journal of Auto-vehicle Safety Association
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• v.14 no.2
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• pp.39-44
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• 2022

This paper presents LiDAR static obstacle map based vehicle position correction algorithm for urban autonomous driving. Real Time Kinematic (RTK) GPS is commonly used in highway automated vehicle systems. For urban automated vehicle systems, RTK GPS have some trouble in shaded area. Therefore, this paper represents a method to estimate the position of the host vehicle using AVM camera, front camera, LiDAR and low-cost GPS based on Extended Kalman Filter (EKF). Static obstacle map (STOM) is constructed only with static object based on Bayesian rule. To run the algorithm, HD map and Static obstacle reference map (STORM) must be prepared in advance. STORM is constructed by accumulating and voxelizing the static obstacle map (STOM). The algorithm consists of three main process. The first process is to acquire sensor data from low-cost GPS, AVM camera, front camera, and LiDAR. Second, low-cost GPS data is used to define initial point. Third, AVM camera, front camera, LiDAR point cloud matching to HD map and STORM is conducted using Normal Distribution Transformation (NDT) method. Third, position of the host vehicle position is corrected based on the Extended Kalman Filter (EKF).The proposed algorithm is implemented in the Linux Robot Operating System (ROS) environment and showed better performance than only lane-detection algorithm. It is expected to be more robust and accurate than raw lidar point cloud matching algorithm in autonomous driving.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.27 no.2
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• pp.353-360
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• 2017

The Internet of Things(IoT) security has more need than a technical problem as it needs series of regulations and faultless security system for common purposes. So, this study proposes an efficient key management in order that can be trusted IoT data in cloud computing. In contrast with a key distribution center of existing sensor networks, the proposed a federation key management of cloud proxy key server is not central point of administration and enables an active key recovery and update. The proposed key management is not a method of predetermined secret keys but sharing key information of a cloud proxy key server in autonomous cloud, which can reduce key generation and space complexity. In addition, In contrast with previous IoT key researches, a federation key of cloud proxy key server provides an extraction ability from meaningful information while moving data.