• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2010.04a
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• pp.379-380
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• 2010

GIS has the basic ability to process high-dense and precise digital data like LiDAR. But the software that common users can use when necessary is expensive and practically impossible for actual use. Thus this study set out to research the methodologies to process and service time series LiDAR data for landslide monitoring.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.36-43
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• 2021

In this research, the accuracy of YOLO v3 algorithm in object detection during AGV (Automated Guided Vehicle) operation was investigated. First of all, AGV with 2D LiDAR and stereo camera was prepared. AGV was driven along the route scanned with SLAM (Simultaneous Localization and Mapping) using 2D LiDAR while front objects were detected through stereo camera. In order to evaluate the accuracy of YOLO v3 algorithm, recall, AP (Average Precision), and mAP (mean Average Precision) of the algorithm were measured with a degree of machine learning. Experimental results show that mAP, precision, and recall are improved by 10%, 6.8%, and 16.4%, respectively, when YOLO v3 is fitted with 4000 training dataset and 500 testing dataset which were collected through online search and is trained additionally with 1200 dataset collected from the stereo camera on AGV.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.3
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• pp.199-205
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• 2007

In this study, we have intended to precisely analyze the aspect of propagation and the extent of damage due to the traffic noise as hon as a main source of noise in urban area. The propagation of traffic noise has a strong relationship between distance and shape of surface. Thus, it is necessary to consider the distribution of buildings for estimating effects of noise in urban area because noise propagations will be affected by buildings. For this, we developed the DEM and DBM using the airborne LiDAR data in the study area and compared with results from the noise simulations using the each model. The extent of damage occurred by the traffic noise above 60 dB(A) from the case of DEM were shown at the 60% of a whole study area, whereas the extent from other case of DBM were shown at the 30% of a whole study area. Also, the extent of the noise levels between 45 dB(A) and 50 dB(A) will be generally recognized as calm environment was increased(the 0% to the 43%) in the case which simulated with building informations. These results indicated that the shape informations of buildings like a DBM is a essential source to simulate the propagation of traffic noise in urban area especially. With results in this study, the effect of traffic noise at a specific area will be easily and precisely estimated if we have the LiDAR data and a traffic census for Korea. Furthermore specific area's traffic noise simulation could be possible using only road traffic information once we have DBM data from LiDAR surveying. This also could be applied as a base data for noise pollution petitioning, traffic planning, construction, etc. in huge city planning projects like a U-City.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.5D
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• pp.527-532
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• 2012

Terrestrial LiDAR emerges as a main mapping technology for indoor 3D cadastre, cultural heritage conservation and, building management in that it provides fast, accurate, and reliable 3D data. In this paper, a new 3D modeling method consisting of segmentation stage and outline extraction stage is proposed to develop indoor 3D model from the terrestrial LiDAR. In the segmentation process, RANSAC and a refinement grid is used to identify points that belong to identical planar planes. In the outline tracing process, a tracing grid and a data conversion method are used to extract outlines of indoor 3D models. However, despite of an improvement of productivity, the proposed approach requires an optimization process to adjust parameters such as a threshold of the RANSAC and sizes of the refinement and outline extraction grids. Furthermore, it is required to model curvilinear and rounded shape of the indoor structures.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2530-2544
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• 2018

In this paper, we propose an enhanced LiDAR-camera calibration method that extracts the marker plane from 3D point cloud information. In previous work, we estimated the straight line of each board to obtain the vertex. However, the errors in the point information in relation to the z axis were not considered. These errors are caused by the effects of user selection on the board border. Because of the nature of LiDAR, the point information is separated in the horizontal direction, causing the approximated model of the straight line to be erroneous. In the proposed work, we obtain each vertex by estimating a rectangle from a plane rather than obtaining a point from each straight line in order to obtain a vertex more precisely than the previous study. The advantage of using planes is that it is easier to select the area, and the most point information on the board is available. We demonstrated through experiments that the proposed method could be used to obtain more accurate results compared to the performance of the previous method.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.177-186
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• 2021

For disaster management and mitigation of earthquakes in Korea Peninsula, active fault investigation has been conducted for the past 5 years. In particular, investigation of sediment-covered active faults integrates geomorphological analysis on airborne LiDAR data, surface geological survey, and geophysical exploration, and unearths subsurface active faults by trench survey. However, the fault traces revealed by trench surveys are only available for investigation during a limited time and restored to the previous condition. Thus, the geological data describing the fault trench sites remain as the qualitative data in terms of research articles and reports. To extend the limitations due to temporal nature of geological studies, we utilized a terrestrial LiDAR to produce 3D point clouds for the fault trench sites and restored them in a digital space. The terrestrial LiDAR scanning was conducted at two trench sites located near the Yangsan Fault and acquired amplitude and reflectance from the surveyed area as well as color information by combining photogrammetry with the LiDAR system. The scanned data were merged to form the 3D point clouds having the average geometric error of 0.003 m, which exhibited the sufficient accuracy to restore the details of the surveyed trench sites. However, we found more post-processing on the scanned data would be necessary because the amplitudes and reflectances of the point clouds varied depending on the scan positions and the colors of the trench surfaces were captured differently depending on the light exposures available at the time. Such point clouds are pretty large in size and visualized through a limited set of softwares, which limits data sharing among researchers. As an alternative, we suggested Potree, an open-source web-based platform, to visualize the point clouds of the trench sites. In this study, as a result, we identified that terrestrial LiDAR data can be practical to increase reproducibility of geological field studies and easily accessible by researchers and students in Earth Sciences.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.185-185
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• 2011

Mapping of artificial levee lines, one of major tasks in river zone mapping, is critical to prevention of river flood, protection of environments and eco systems in river zones. Thus, mapping of artificial levee lines is essential for management and development of river zones. Coastal mapping including river zone mapping has been historically carried out using surveying technologies. Photogrammetry, one of the surveying technologies, is recently used technology for national river zone mapping in Korea. Airborne laser scanning has been used in most advanced countries for coastal mapping due to its ability to penetrate shallow water and its high vertical accuracy. Due to these advantages, use of LiDAR data in coastal mapping is efficient for monitoring and predicting significant topographic change in river zones. This paper introduces a method for construction of a 3D artificial levee line using a set of LiDAR points that uses normal vectors. Multiple steps are involved in this method. First, a 2.5-dimensional Delaunay triangle mesh is generated based on three nearest-neighbor points in the LiDAR data. Second, a median filtering is applied to minimize noise. Third, edge selection algorithms are applied to extract break edges from a Delaunay triangle mesh using two normal vectors. In this research, two methods for edge selection algorithms using hypothesis testing are used to extract break edges. Fourth, intersection edges which are extracted using both methods at the same range are selected as the intersection edge group. Fifth, among intersection edge group, some linear feature edges which are not suitable to compose a levee line are removed as much as possible considering vertical distance, slope and connectivity of an edge. Sixth, with all line segments which are suitable to constitute a levee line, one river levee line segment is connected to another river levee line segment with the end points of both river levee line segments located nearest horizontally and vertically to each other. After linkage of all the river levee line segments, the initial river levee line is generated. Since the initial river levee line consists of the LiDAR points, the pattern of the initial river levee line is being zigzag along the river levee. Thus, for the last step, a algorithm for smoothing the initial river levee line is applied to fit the initial river levee line into the reference line, and the final 3D river levee line is constructed. After the algorithm is completed, the proposed algorithm is applied to construct the 3D river levee line in Zng-San levee nearby Ham-Ahn Bo in Nak-Dong river. Statistical results show that the constructed river levee line generated using a proposed method has high accuracy in comparison to the ground truth. This paper shows that use of LiDAR data for construction of the 3D river levee line for river zone mapping is useful and efficient; and, as a result, it can be replaced with ground surveying method for construction of the 3D river levee line.

• 한국지형공간정보학회:학술대회논문집
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• 2004.10a
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• pp.123-128
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• 2004

최근 디지털 카메라(Digital camera), 다중/고분광 영상(Mumltispectral/Hyperspectral image), LiDAR(Light Detection and Ranging), InSAR(Interferometric SAR)와 같이 지상을 보다 상세하고 높은 정확도로 지상을 매핑할 수 있는 센서들이 출현하고 있다. 이러한 다양한 정보 취득 자료를 충분히 활용하여 통합하기 위해서는 영상에 대하여 정확한 기하보정 또는 정사영상의 제작과 LiDAR 자료와 같은 경우 평면위치의 오차를 조정하여 다중자료들 간의 정확한 지형보정(Coregistration)이 필요하다. 본 연구에서는 AIR-MS 자료를 이용하여 즉, 항공기로부터 취득한 LiDAR(Height와 강도(Intensity) 자료), digital camera을 통합하고, 기존의 컬러항공사진 및 1:1000 수치지도를 이용하여 3D GIS 자료의 생성을 시도하였다.

• ETRI Journal
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• v.45 no.5
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• pp.836-846
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• 2023

Mobile robots are used in modern life; however, object recognition is still insufficient to realize robot navigation in crowded environments. Mobile robots must rapidly and accurately recognize the movements and shapes of pedestrians to navigate safely in pedestrian-rich spaces. This study proposes real-time, accurate, three-dimensional (3D) multi-pedestrian detection and tracking using a 3D light detection and ranging (LiDAR) point cloud in crowded environments. The pedestrian detection quickly segments a sparse 3D point cloud into individual pedestrians using a lightweight convolutional autoencoder and connected-component algorithm. The multi-pedestrian tracking identifies the same pedestrians considering motion and appearance cues in continuing frames. In addition, it estimates pedestrians' dynamic movements with various patterns by adaptively mixing heterogeneous motion models. We evaluate the computational speed and accuracy of each module using the KITTI dataset. We demonstrate that our integrated system, which rapidly and accurately recognizes pedestrian movement and appearance using a sparse 3D LiDAR, is applicable for robot navigation in crowded spaces.

• The Journal of Korea Robotics Society
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• v.10 no.1
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• pp.33-41
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• 2015

Recent developments in robotics and intelligent vehicle area, bring interests of people in an autonomous driving ability and advanced driving assistance system. Especially fully automatic parking ability is one of the key issues of intelligent vehicles, and accurate parked vehicles detection is essential for this issue. In previous researches, many types of sensors are used for detecting vehicles, 2D LiDAR is popular since it offers accurate range information without preprocessing. The L shape feature is most popular 2D feature for vehicle detection, however it has an ambiguity on different objects such as building, bushes and this occurs misdetection problem. Therefore we propose the accurate vehicle detection method by using a 3D complete vehicle model in 3D point clouds acquired from front inclined 2D LiDAR. The proposed method is decomposed into two steps: vehicle candidate extraction, vehicle detection. By combination of L shape feature and point clouds segmentation, we extract the objects which are highly related to vehicles and apply 3D model to detect vehicles accurately. The method guarantees high detection performance and gives plentiful information for autonomous parking. To evaluate the method, we use various parking situation in complex urban scene data. Experimental results shows the qualitative and quantitative performance efficiently.