• Journal of Internet Computing and Services
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• v.23 no.6
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• pp.71-78
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• 2022

This paper proposes an algorithm for 3D object detection by processing point cloud data of 3D LiDAR. Unlike 2D LiDAR, 3D LiDAR-based data was too vast and difficult to process in three dimensions. This paper introduces various studies based on 3D LiDAR and describes 3D LiDAR data processing. In this study, we propose a method of processing data of 3D LiDAR using clustering techniques for object detection and design an algorithm that fuses with cameras for clear and accurate 3D object detection. In addition, we study models for clustering 3D LiDAR-based data and study hyperparameter values according to models. When clustering 3D LiDAR-based data, the DBSCAN algorithm showed the most accurate results, and the hyperparameter values of DBSCAN were compared and analyzed. This study will be helpful for object detection research using 3D LiDAR in the future.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.135-145
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• 2022

This study aims to verify the Drone utilization and the accuracy of the global navigation satellite system (GNSS), Drone RGB (Photogrammetry) (D-RGB), and Drone LiDAR (D-LiDAR) surveying performance in the downstream reaches of the local stream. The results of the measurement of Ground Control Point (GCP) and Check Point (CP) coordinates confirmed the excellence. This study was carried out by comparing GNSS, D-RGB, and D-LiDAR with the values which the hydraulic characteristics calculated using HEC-RAS model. The accuracy of three survey methods was compared in the area of the study which is the ownership station, to 6 GCP and 3 CP were installed. The comparison results showed that the D-LiDAR survey was excellent. The 100-year frequency design flood discharge was applied in the channel sections of the small stream. As a result of D-RGB surveying 2.30 m and D-LiDAR 1.80 m in the average bed elevation, and D-RGB surveying 4.73 m and D-LiDAR 4.25 m in the average flood condition. It is recommended that the performance of D-LiDAR surveying is efficient method and useful as the surveying technique of the geospatial information using the drone equipment in stream channel.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.4
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• pp.443-452
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• 2008

To deduce 3D linear information which express shapes of buildings out of airphoto by fusion of airphoto and LiDAR data, this research went through 2 process. First, research made LiDAR data into projected data of 2D based on airphoto. For this, the virtual points were added to solve the visual problem of building boundary area which has poor information because the attribute in LiDAR data. Research construct irregular triangular nets from modified LiDAR data and judge visual triangular nets out of image. Through this, research can make reference to information of triangular nets in each image pixel. Second, 3D information was extracted from stereo images segments by combining extracted information of visible region and 2D irregular triangular nets. Matching way based on TIN for segments from stereo images was used. Matching condition based on TIN can improve about 20% of edge matching accuracy compared to existing quadrilateral condition of epipolar geometry.

• 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 Korean Society for Geospatial Information Science
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• v.19 no.2
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• pp.3-8
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• 2011

Recently, the demand for enterprise for service map providing and portal site services of a 3D virtual city model for public users has been expanding. Also, accuracy of the data, transfer rate and the update for the update for the lapse of time emerge are considered as more impertant factors, by providing 3D information with the web or mobile devices. With the latest technology, we have seen various 3D data through the web. With the VRML progressing actively, because it can provide a virtual display of the world and all aspects of interaction with web. It offers installation of simple plug-in without extra cost on the web. LiDAR system can obtain spatial data easily and accurately, as supprted by numerous researches and applications. However, in general, LiDAR data is obtained in the form of an irregular point cloud. So, in case of using data without converting, high processor is needed for presenting 2D forms from point data composed of 3D data and the data increase. This study expresses urban LiDAR data in 3D, 2D raster data that was applied by compressing algorithm that was used for solving the problems of large storage space and processing. For expressing 3D, algorithm that converts compressed LiDAR data into code Suited to VRML was made. Finally, urban area was expressed in 3D with expressing ground and feature separately.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.2
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• pp.419-424
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• 2009

This paper show about the possibility of practical application after building VR(virtual reality) data based on Airborne LiDAR data which determines complicated topography quickly for the 3D-GIS construction. In this paper, we collected Airborne LiDAR data, digital map, serial photo and a basic design. The results are expected some effective determination by 3D-GIS construction based on LiDAR data. Hereafter, because the research will be able to be given quickly topography information on ubiquitous environment the field of construction and GIS will be able to be helped.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.27 no.3
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• pp.401-408
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• 2009

A study for 3D-reconstruction and providing the geospatial information is in progress to many fields recently. For efficient providing the geospatial information, the present information has to be updated and be revised and then the latest geospatial information needs to be acquired economically. Especially, LiDAR system utilized in many study has a advantage to collect the 3D spacial data easily and densely that is possible to supply to the geospatial information. The 3D data of LiDAR is very suitable as a data for presenting 3D space, but in case of using the data without converting, the high performance processor is needed for presenting 2D forms from point data composed by 3D data. In comparison, basically the raster data structure of 2D form is more efficient than vector structure in cheap devices because of a simple structure and process speed. The purpose of this study, in case of supplying LiDAR data as 3D data, present the method that reconstructs to 2D raster data and convert to compression data applied by th tree construction in detail.

• Journal of Digital Contents Society
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• v.18 no.5
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• pp.989-994
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• 2017

In this paper, we propose a pothole detection system using 2D LiDAR and a pothole detection algorithm. Conventional pothole detection methods can be divided into vibration-based method, 3D reconstruction method, and vision-based method. Proposed pothole detection system uses two inexpensive 2D LiDARs and improves pothole detection performance. Pothole detection algorithm is divided into preprocessing for noise reduction, clustering and line extraction for visualization, and gradient function for pothole decision. By using gradient of distance data function, we check the existence of a pothole and measure the depth and width of the pothole. The pothole detection system is developed using two LiDARs, and the 3D pothole detection performance is shown by detecting a pothole with moving LiDAR system.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.1865-1873
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• 2017

The feature-based visual SLAM requires 3D positions for the extracted feature points to perform 3D-2D motion estimation. LiDAR can provide reliable and accurate 3D position information with low computational burden, while stereo camera has the problem of the impossibility of stereo matching in simple texture image region, the inaccuracy in depth value due to error contained in intrinsic and extrinsic camera parameter, and the limited number of depth value restricted by permissible stereo disparity. However, the sparsity of LiDAR data may increase the inaccuracy of motion estimation and can even lead to the result of motion estimation failure. Therefore, in this paper, we propose three interpolation methods which can be applied to interpolate sparse LiDAR data. Simulation results obtained by applying these three methods to a visual odometry algorithm demonstrates that the selective bilinear interpolation shows better performance in the view point of computation speed and accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.4
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• pp.253-265
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• 2016

We propose an obstacle classification method using multi-decision factors and decision sections based on Single 2D LiDAR. The existing obstacle classification method based on single 2D LiDAR has two specific advantages: accuracy and decreased calculation time. However, it was difficult to classify obstacle type, and therefore accurate path planning was not possible. To overcome this problem, a method of classifying obstacle type based on width data was proposed. However, width data was not sufficient to enable accurate obstacle classification. The proposed algorithm of this paper involves the comparison between decision factor and decision section to classify obstacle type. Decision factor and decision section was determined using width, standard deviation of distance, average normalized intensity, and standard deviation of normalized intensity data. Experiments using a real autonomous vehicle in a real environment showed that calculation time decreased in comparison with 2D LiDAR-based method, thus demonstrating the possibility of obstacle type classification using single 2D LiDAR.