• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.25-32
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• 2005

This paper presents a method for point-based 3D building reconstruction using Lidar data and digital map. The proposed method consists of three processes: extraction of building roof points, identification of roof types, and 3D building reconstruction. After extracting points inside the polygon of building, the ground surface, wall and tree points among the extracted points are removed through the filtering process. The filtered points are then fitted into the flat plane using ODR(Orthogonal Distance Regression) in the first place. If the fitting error is within the predefined threshold, the surface is classified as a flat roof. Otherwise, the surface is fitted and classified into a gable or arch roof through RMSE analysis. Experimental results showed that the proposed method classified successfully three different types of roof and that the fusion of LIDAR data and digital map could be a feasible method of modeling 3D building reconstruction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.3
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• pp.311-320
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• 2008

A LIDAR can rapidly generate 3D points by densely sampling the surfaces of targets using laser pulses, which has been efficiently utilized to reconstruct 3D models of the targets automatically. Due to this advantage, LIDARs are increasingly applied to the fields of Defense and Security, for examples, being employed to intelligently guided missiles and manned/unmanned reconnaissance planes. For the prior verification of the LIDAR applicability, this study aims at generating simulated LIDAR data. Here, we derived the sensor equation by modelling the geometric relationships between the LIDAR sub-modules, such as GPS, IMU, LS and the systematic errors associated with them. Based on this equation, we developed a program to generate simulated data with the system parameters, the systematic errors, the flight trajectories and attitudes, and the reference terrain model given. This program had been applied to generating simulated LIDAR data for urban areas. By analyzing these simulated data, we verified the accuracy and usefulness of the simulation. The simulator developed in this study will provide economically various test data required for the development of application algorithms and contribute to the optimal establishment of the flight and system parameters.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.400-403
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• 2021

Algorithms for predicting the optimal route of vehicles are being actively sudied with the recent development of autonomous driving technology. Companies such as SK, Kakao, and Naver provide services that navigate the optimal route. They predicts the optimal path with information from the users in real time. However, they can predict the optimal route, but not optimal lane route. We proposes a system that navigates the optimal lane path with coordinates data from vehicles using Lidar sensor. The proposed method is a system that guides smooth lanes by acquiring time series coordinate data of a vehicle after performing the Lidar-based object detection method. we demonstrates the performance using actual acquired data from the experimental results.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.13-22
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• 2006

Realistic 3D building construction in urban area has become an important issue because of increasing demand of 3D geo-spatial information in many application. Contrary to the conventional 3D building model construction approach using aerial images and high-resolution satellite imagery, it has been researched widely in building reconstruction using high-accuracy aerial LIDAR data in the latest. This paper presents a method for 3D building construction through building outlines extraction by LoG operator's Zero-crossing and line generation and refinement by Douglas-Peucker algorithm.

• ETRI Journal
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• v.33 no.4
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• pp.506-516
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• 2011

In this paper, we develop a registration method to eliminate the geometric inconsistency between the stereo-images and light detection and ranging (LIDAR) data obtained by an airborne multisensor system. This method consists of three steps: registration primitive extraction, correspondence establishment, and exterior orientation parameter (EOP) adjustment. As the primitives, we employ object points and linked edges from the stereo-images and planar patches and intersection edges from the LIDAR data. After extracting these primitives, we establish the correspondence between them, being classified into vertical and horizontal groups. These corresponding pairs are simultaneously incorporated as stochastic constraints into aerial triangulation based on the bundle block adjustment. Finally, the EOPs of the images are adjusted to minimize the inconsistency. The results from the application of our method to real data demonstrate that the inconsistency between both data sets is significantly reduced from the range of 0.5 m to 2 m to less than 0.05 m. Hence, the results show that the proposed method is useful for the data fusion of aerial images and LIDAR data.

• Journal of Korea Multimedia Society
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• v.24 no.11
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• pp.1518-1525
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• 2021

Due to the growth of VR industry and rise of digital twin industry, the importance of implementing 3D data same as real space is increasing. However, the fact that it requires expertise personnel and huge amount of time is a problem. In this paper, we propose a system that generates point cloud data with same shape and color as a real space, just by scanning the space. The proposed system integrates 3D geometric information from lidar and color information from stereo camera into one point cloud. Since the number of 3D points generated by lidar is not enough to express a real space with good quality, some of the pixels of 2D image generated by camera are mapped to the correct 3D coordinate to increase the number of points. Additionally, to minimize the capacity, overlapping points are filtered out so that only one point exists in the same 3D coordinates. Finally, 6DoF pose information generated from lidar point cloud is replaced with the one generated from camera image to position the points to a more accurate place. Experimental results show that the proposed system easily and quickly generates point clouds very similar to the scanned space.

• Atmosphere
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• v.21 no.1
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• pp.57-67
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• 2011

Aerosol lidar ratio (extinction-to-backscatter ratio) at 532 nm was determined using 4-year measurements of elastic-backscatter lidar and sky radiometer at Seoul National University of Seoul, Korea. The mean lidar ratio (with standard deviation) based on 4 years of measurements is found to be $61.7{\pm}16.5$ sr, and weak seasonal variations are noted with a maximum in JJA ($68.1{\pm}16.8$ sr) and a minimum in DJF ($57.2{\pm}17.9$ sr). The lidar ratios for clean, dust, and polluted conditions are estimated to be $45.0{\pm}9.5$ sr, $51.7{\pm}13.7$ sr, and $62.2{\pm}13.2$ sr, respectively. While the lidar ratio for the polluted condition is appears to be consistent with previous studies, clean and dust conditions tend to have larger ratios, compared to previous estimates. This discrepancy is thought to be mainly due to the anthropogenic aerosols existing throughout the year around Seoul, which may cause increased lidar ratios even for clean and dust conditions.

• Korean Journal of Geomatics
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• v.3 no.2
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• pp.107-114
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• 2004

The National Geographic Information Institute (NGII) in korea, through the National Geographic Information System (NGIS) Program, has prepared to generate and disseminate digital elevation data for Korea. This is a pilot research to propose a policy for production, maintenance, and supply of Korea Digital Elevation Data(KDED). Customer demands for accuracy and resolution of DEM was surveyed through a questionnaire. In order to investigate the quality, the technical efficiency and the production cost, a tentative DEM in a small test site was generated based on digital topographic maps (original paper map scale 1:5,000), analytical plotter, and LIDAR. The Accuracy standard for KDED was derived based on source data generation methods. As a result of this research, a uniformly spaced grid model was recommended for KDED. Its preferable grid space is 5m in urban areas and its vicinity, and 10m in field and mountainous area. LIDAR has been valuated as a proper KDED generation method fulfilling customers' demands for the accuracy.

• Journal of Positioning, Navigation, and Timing
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• v.9 no.1
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• pp.23-31
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• 2020

It is essential to estimate the vehicle localization for an autonomous safety driving. In particular, since LIDAR provides precise scan data, many studies carried out to estimate the vehicle localization using LIDAR and pre-generated map. The road marking always exists on the road because of provides driving information. Therefore, it is often used for map information. In this paper, we propose to generate the Gaussian mixture map based on road-marking information and localization method using this map. Generally, the probability distributions map stores the single Gaussian distribution for each grid. However, single resolution probability distributions map cannot express complex shapes when grid resolution is large. In addition, when grid resolution is small, map size is bigger and process time is longer. Therefore, it is difficult to apply the road marking. On the other hand, Gaussian mixture distribution can effectively express the road marking by several probability distributions. In this paper, we generate Gaussian mixture map and perform vehicle localization using Gaussian mixture map. Localization performance is analyzed through the experimental result.

• Journal of the Optical Society of Korea
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• v.14 no.3
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• pp.185-189
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• 2010

A micro-pulse LIDAR system (MPL) was employed to measure the aerosol over Pudong, Shanghai from July 2008 to January 2009. Based on Fernald method, aerosol optical variables such as extinction coefficient were retrieved and analyzed. Results show that aerosol exists mainly in low layers; aerosol loading reaches its maximum in the afternoon, and then decreases with time until its minimum at night. Most of the aerosol concentrates in the layer below 3 km, and optical extinction coefficient in the layer below 2 km contributes 84.25% of that below 6 km. Two extinction coefficient peaks appear in the near surface layer up to 500 m and in the level around 1000 m. Aerosol extinction coefficient shows a seasonal downward trend from summer to winter.