• KSCE Journal of Civil and Environmental Engineering Research
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• v.41 no.4
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• pp.469-475
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• 2021

In order to effectively maintain and manage river facilities, on going data collection of associated objects is important. However, the existing data acquisition methods of using a total station, a global navigation satellite system, or a terrestrial laser scanner have limitations in terms of cost/time/manpower when acquiring spatial information data on river facilities distributed over a wide and long area, unlike general facilities. In contrast, a mobile mapping system (MMS), which acquires data while moving its platform, acquires precise spatial information data for a large area in a short time, so it is suitable for use in the maintenance of linear facilities around rivers. As a result of applying a MMS to a research area of 4 km, 184,646,099 points were acquired during a 20-minute data acquisition period, and 378 cross-sections were extracted. By comparing this with computer-drawn river plans, it was confirmed that efficient levee management using a MMS is possible.

• Spatial Information Research
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• v.13 no.4 s.35
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• pp.373-380
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• 2005

Mobile Mapping Systems are effective systems to acquire the position and image data using vehicle equipped with the GPS (Global Positioning System), IMU (Inertial Measurement Unit), and CCD camera. They are used in various fields of road facility management, map update, and etc. In the general photogrammetry such as aerial photogrammetry, GCP (Ground Control Point)s are needed to compute the image exterior orientation elements (the position and attitude of camera). These points are measured by field survey at the time of data acquisition. But it costs much time and money. Moreover, it is not possible to make sufficient GCP as much as we want. However Mobile Mapping Systems are more efficient both in time and money because they can obtain the position and attitude of camera at the time of photographing. That is, Image Orientation Technique must use GCP to compute the image exterior orientation elements, but on the other hand Direct Georeferencing can directly compute the image exterior orientation elements by GPS/INS. In this paper, we analyze about the positional accuracy comparison of ground point using the Image Orientation Technique and Direct Georeferencing Technique.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.36-41
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• 2017

The mobile mapping system first introduced at Ohio State University in 1991 is being developed in various forms as sensor technology develops. The mobile mapping system can acquire geospatial information around amoving object quickly using the information gathered using the position and attitude information of the moving object and the data from various sensors. The mobile mapping system can rapidly acquire large amounts of Geospatial information and MMS provides maximum productivity in the same measurement methods as existing GNSS and total stations. Currently, a variety of systems are being launched, mainly by foreign companies, and they are applied to the construction of geospatial information. On the other hand, the application of domestic technology development or production is insufficient. This paper provides basic data for the introduction of a mobile mapping system to geospatial information related business by conducting the status survey and feature analysis of a commercialized system focusing on the ground-based mobile mapping system. The research identified the current status and characteristics of high-priced, low-priced, indoor, and handheld mobile mapping systems based on vehicles and suggest that the recent system development trends are moving toward lowering the unit prices. The mobile mapping system is currently being developed as a platform for the application of geospatial information construction and the launch of low-cost models. The development of data processing technologies, such as automatic matching and the launch of low-cost models, are forming a basis for the application of mobile mapping systems in the field of geospatial information construction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.26 no.6
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• pp.611-616
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• 2008

When extracting geo-referenced 3D data from cameras mounted on Mobile Mapping Systems, one of important properties for accuracy of extracted data is the alignment of the relative translation(lever-arm) and rotation(bore-sight) between the coordinate systems of Inertial Measurement Unit(IMU)/Ground Positioning System(GPS) and cameras. Since the conventional method calculates absolute camera orientation using ground control points (GCP), the alignment is determined in one Coordinated System (GPS Coordinated System). It basically require GCP. We proposed a mathematical model for the alignment using the initially uncoupled data of cameras and IMU/GPS without GCPs.

• Journal of the Korean Association of Geographic Information Studies
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• v.11 no.1
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• pp.10-19
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• 2008

This study designed and implemented a J2ME based on mapping viewer to browse the SVG based wireless-map in mobile phone. This proposed technique was efficiently applied to a forest fire extinguishment information management system by mapping the exact location of important objects on wireless-map in wireless network. As the result, the study helps to guide the safe and efficient extinguishment affairs and provides the safe extinguishment environment for ground fire fighting teams in real time. And also this technique presents the way to move the client mapping function such as representation of the moving coordinates to server and made it possible to operate SVG based viewer in personal cellular phone.

• Korean Journal of Remote Sensing
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• v.26 no.5
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• pp.593-603
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• 2010

Most spatial data acquisition systems employing a set of frame cameras may have suffered from their small fields of view and poor base-distance ratio. These limitations can be significantly reduced by employing an omni-directional camera that is capable of acquiring images in every direction. Bundle Block Adjustment (BBA) is one of the existing georeferencing methods to determine the exterior orientation parameters of two or more images. In this study, by extending the concept of the traditional BBA method, we attempt to develop a mathematical model of BBA for omni-directional images. The proposed mathematical model includes three main parts; observation equations based on the collinearity equations newly derived for omni-directional images, stochastic constraints imposed from GPS/INS data and GCPs. We also report the experimental results from the application of our proposed BBA to the real data obtained mainly in urban areas. With the different combinations of the constraints, we applied four different types of mathematical models. With the type where only GCPs are used as the constraints, the proposed BBA can provide the most accurate results, ${\pm}5cm$ of RMSE in the estimated ground point coordinates. In future, we plan to perform more sophisticated lens calibration for the omni-directional camera to improve the georeferencing accuracy of omni-directional images. These georeferenced omni-directional images can be effectively utilized for city modelling, particularly autonomous texture mapping for realistic street view.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.11a
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• pp.193-195
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• 2022

본 논문에서는 3차원 스캔 없이 이미지 입력만을 사용한 개인 체형을 고려한 모바일 가상 착용 시스템의 전체 과정을 설계하고 개발하였다. 이를 위하여 이미지상 인물의 자세와 체형의 추정을 통하여 3차원 인체모델(SMPL)을 추정하는 최근의 방식을 이용하였고, 앞 뒷면 의상 이미지를 2차원 texture 매핑과 평면 triangle mesh로 복원하고 의상 봉제 (sewing) 시뮬레이션을 사용하여 3차원 의상 모델을 생성하는 방법을 새롭게 개발하였다. 또한 이를 활용한 3차원 개인화된 가상 착용 모바일 앱과 서비스를 Flask와 iOS 환경에서 SceneKit을 활용하여 개발하였다. 이를 통하여 단순히 의상의 매칭과 스타일 뿐 아니라 사이즈에 따른 착용 Fit을 구매 전에 확인할 수 있는 전체 서비스를 실현 및 검증하였다.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.535-544
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• 2018

Autonomous driving can be limited by only using sensors if the sensor is blocked by sudden changes in surrounding environments or large features such as heavy vehicles. In order to overcome the limitations, the precise road-map has been used additionally. This study was conducted to segment and classify road objects using 3D point cloud data acquired by terrestrial mobile mapping system provided by National Geographic Information Institute. For this study, the original 3D point cloud data were pre-processed and a filtering technique was selected to separate the ground and non-ground points. In addition, the road objects corresponding to the lanes, the street lights, the safety fences were initially segmented, and then the objects were classified using the support vector machine which is a kind of machine learning. For the training data for supervised classification, only the geometric elements and the height information using the eigenvalues extracted from the road objects were used. The overall accuracy of the classification results was 87% and the kappa coefficient was 0.795. It is expected that classification accuracy will be increased if various classification items are added not only geometric elements for classifying road objects in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.243-251
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• 2019

The road sign location information installed on national roads is continuously updated using MMS (Mobile Mapping System) technology. It is possible to map accurate road facilities by MMS, but the equipment is very expensive and requires specialized technology. Also, the accuracy of the position of the object greatly depends on the GPS (Global Positioning System) accuracy. In the case of road facility mapping, the advantage of drone is more remarkable than that of field survey or conventional aerial photogrammetry. In particular, it is more efficient than field surveying and it is possible to acquire high resolution images with low budget compared to conventional aerial photogrammetry. In this study, the accuracy of the location information measured by the existing MMS is compared with the GPS survey result and the accuracy analysis is performed by the drone aerial photogrammetry. In order to confirm the space accuracy that can be obtained when conducting drone aerial photogrammetry, the accuracy of the change in the number of ground control points and the degree of overlap was evaluated. As a result of the experiment, it was possible to obtain sufficient accuracy with two ground control points distributed at both ends of the road and 60% overlap.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.3
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• pp.305-315
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• 2010

This research aims to develop a method to determine the 3D coordinates of an object point from overlapping omni-directional images acquired by a ground mobile mapping system and assess their accuracies. In the proposed method, we first define an individual coordinate system on each sensor and the object space and determine the geometric relationships between the systems. Based on these systems and their relationships, we derive a straight line of the corresponding object point candidates for a point of an omni-directional image, and determine the 3D coordinates of the object point by intersecting a pair of straight lines derived from a pair of matched points. We have compared the object coordinates determined through the proposed method with those measured by GPS and a total station for the accuracy assessment and analysis. According to the experimental results, with the appropriate length of baseline and mutual positions between cameras and objects, we can determine the relative coordinates of the object point with the accuracy of several centimeters. The accuracy of the absolute coordinates is ranged from several centimeters to 1 m due to systematic errors. In the future, we plan to improve the accuracy of absolute coordinates by determining more precisely the relationship between the camera and GPS/INS coordinates and performing the calibration of the omni-directional camera