• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.4
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• pp.287-293
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• 2018

It is prerequisite to generate epipolar resampled images by reducing the y-parallax for accurate and efficient processing of satellite stereo images. Minimizing y-parallax requires the accurate sensor modeling that is carried out with ground control points. However, the approach is not feasible over inaccessible areas where control points cannot be easily acquired. For the case, a relative orientation can be utilized only with conjugate points, but its accuracy for satellite sensor should be studied because the sensor has different geometry compared to well-known frame type cameras. Therefore, we carried out the bias-compensation of RPCs (Rational Polynomial Coefficients) without any ground control points to study its precision and effects on the y-parallax in epipolar resampled images. The conjugate points were generated with stereo image matching with outlier removals. RPCs compensation was performed based on the affine and polynomial models. We analyzed the reprojection error of the compensated RPCs and the y-parallax in the resampled images. Experimental result showed one-pixel level of y-parallax for Kompsat-3 stereo data.

• Korean Journal of Construction Engineering and Management
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• v.10 no.6
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• pp.3-12
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• 2009

In order to effectively distribute the resources, it is very critical to understand the status or progress of construction site quickly and accurately. Augmented Reality (AR) can provide this situation with information which is convenient and intuitive. Conventional implementation of AR in outdoor or construction site condition requires additional sensors or markers to track the position and direction of camera. This research is aimed to develop the technologies which can be utilized in gathering the information of constructing or constructed buildings and structures. The AR technique that does not require additional devices except for the camera was implemented to simplify the system and improve utility in inaccessible area. In order to do so, the position of camera's perspective center and direction of camera was estimated using exterior orientation techniques. And 3D drawing model of building was projected and overlapped using this information. The result shows that by using this technique, the virtual drawing image was registered on real image with few pixels of error. The technique and procedure introduced in this paper simplifies the hardware organization of AR system that makes it easier for the AR technology to be utilized with ease in construction site. Moreover, this technique will help the AR to be utilized even in inaccessible areas. In addition to this, it is expected that combining this technique and 4D CAD technology can provide the project manager with more intuitive and comprehensive information that simplifies the monitoring work of construction progress and planning.

• Journal of Korea Water Resources Association
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• v.49 no.6
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• pp.469-480
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• 2016

The present study aims to develop a real-time surface image velocimeter (SIV) using an Android smartphone. It can measure river surface velocity by using its built-in sensors and processors. At first the SIV system figures out the location of the site using the GPS of the phone. It also measures the angles (pitch and roll) of the device by using its orientation sensors to determine the coordinate transform from the real world coordinates to image coordinates. The only parameter to be entered is the height of the phone from the water surface. After setting, the camera of the phone takes a series of images. With the help of OpenCV, and open source computer vision library, we split the frames of the video and analyzed the image frames to get the water surface velocity field. The image processing algorithm, similar to the traditional STIV (Spatio-Temporal Image Velocimeter), was based on a correlation analysis of spatio-temporal images. The SIV system can measure instantaneous velocity field (1 second averaged velocity field) once every 11 seconds. Averaging this instantaneous velocity measurement for sufficient amount of time, we can get an average velocity field. A series of tests performed in an experimental flume showed that the measurement system developed was greatly effective and convenient. The measured results by the system showed a maximum error of 13.9 % and average error less than 10 %, when we compared with the measurements by a traditional propeller velocimeter.

• Spatial Information Research
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• v.18 no.5
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• pp.37-45
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• 2010

AT(Aerial Triangulation) is the essential procedure for creating orthophoto and transforming coordinates on the photographs into the real world coordinates utilizing GCPs (Ground Control Point) which is obtained by field survey and the external orientation factors from GPS/INS as a reference coordinates. In this procedure, all of the GCPs can be collected from field survey using GPS and Total Station, or obtained from digital maps. Collecting GCPs by field survey is accurate than GCPs from digital maps; however, lots of manpower should be put into the collecting procedure, and time and cost as well. On the other hand, in the case of obtaining GCPs from digital maps, it is very difficult to secure the required accuracy because almost things at each stage in the collecting procedure should rely on the subjective judgement of the performer. In this study, the results from three methods have been compared for the accuracy assessment in order to know if the results of each case is within the allowance error: for the perceivable objects such as road boarder, speed bumps, constructions etc., 1) GCPs selection utilizing the unique LiDAR intensity value reflected from such objects, 2) using LiDAR DSM and 3) GCPs from field survey. And also, AT and error analysis have been carried out w ith GCPs obtained by each case.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.35 no.6
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• pp.535-544
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• 2017

UAVs (Unmanned Aerial Vehicle) are generally classified into fixed-wing and rotary-wing type, and both have very different flight characteristics each other during photographing. These can greatly effect on the quality of images and their productions. In this paper, the change of the camera rotation angle at the moment of photographing was compared and analyzed by calculating orientation angles of each image taken by both types of payload. Study materials were acquired at an altitude of 130m and 260m with fixed-wing, and at an altitude of 130m with rotary-wing UAV over an agricultural land. In addition, an accuracy comparison of boundary surveying methods between UAV photogrammetry and terrestrial cadastral surveying was conducted in two parcels of the study area. The study results are summarized as follows. The differences at rotation angles of images acquired with between two types of UAVs at the same flight height of 130m were significantly very large. On the other hand, the distance errors of parcel boundary surveying were not significant between them, but almost the same, about within ${\pm}0.075m$ in RMSE (Root Mean Square Error). The accuracy of boundary surveying with a fixed-wing UAV at 260m altitude was quite variable, $0.099{\sim}0.136m$ in RMSE. In addition, the error of area extracted from UAV-orthoimages was less than 0.2% compared with the results of the cadastral survey in the same two parcels used for the boundary surveying, In conclusion, UAV photogrammetry can be highly utilized in the field of cadastral surveying.

• KIPS Transactions on Software and Data Engineering
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• v.6 no.7
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• pp.337-352
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• 2017

Clone-and-own reuse is an approach to creating new software variants by copying and modifying existing software products. A family of legacy software products developed by clone-and-own reuse often requires high maintenance cost and tends to be error-prone due to patch-ups without refactoring and structural degradation. To overcome these problems, many organizations that have used clone-and-own reuse now want to migrate their legacy products to software product line (SPL) for more systematic reuse and management of software asset. However, with most of existing methods, variation points are embedded directly into design and code rather than modeled and managed separately; variation points are not created ("engineered") systematically based on a variability model. This approach causes the following problems: it is difficult to understand the relationships between variation points, thus it is hard to maintain such code and the asset tends to become error-prone as it evolves. Also, when SPL evolves, design/code assets tend to be modified directly in an ad-hoc manner rather than engineered systematically with appropriate refactoring. To address these problems, we propose a feature-oriented method for extracting a SPL asset from a family of legacy applications. With the approach, we identify and model variation points and their relationships in a feature model separate from implementation, and then extract and manage a SPL asset from legacy applications based on the feature model. We have applied the method to a family of legacy Notepad++ products and demonstrated the feasibility of the method.

• Journal of the Korean Association of Geographic Information Studies
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• v.10 no.1
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• pp.35-46
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• 2007

In the study digital imagery was used to examine asphalt concrete pavements. With digitally mastered-image information that was filmed with a video camera fixed on a car travelling on road at a consistent speed, a road surface management system that can gain road surface information (Crack, Rutting, IRI) was developed using an object-oriented language "Delphi". This system was designed to improve visualized effects by animations and graphs. After analyzing the accuracy of 3-D coordinates of road surfaces that were decided using multiple image orientation and bundle adjustment method, the average of standard errors turned out to be 0.0427m in the X direction, 0.0527m in the Y direction and 0.1539m in the Z direction. As a result, it was found to be good enough to be put to practical use for maps drawn on scales below 1/1000, which are currently producted and used in our country, and GIS data. According to the analysis of the accuracy in crack width on 12 spots using a digital video camera, the standard error was found to be ${\pm}0.256mm$, which is considered as high precision. In order to get information on rutting, the physically measured cross sections of 4 spots were compared with cross sections generated from digital images. Even though a maximum error turned out to be 10.88mm, its practicality is found in work efficiency.

• Korean Journal of Remote Sensing
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• v.35 no.5_2
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• pp.841-850
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• 2019

The purpose of this study is to strengthen the capability of rapid mapping for disaster through improving the positioning accuracy of mapping and fusion of multi-sensing point cloud data derived from Unmanned Aerial Vehicles (UAVs) and disaster investigation vehicle. The positioning accuracy was evaluated for two procedures of drone mapping with Agisoft PhotoScan: 1) general geo-referencing by self-calibration, 2) proposed geo-referencing with optimized camera model by using fixed accurate Interior Orientation Parameters (IOPs) derived from indoor camera calibration test and bundle adjustment. The analysis result of positioning accuracy showed that positioning RMS error was improved 2~3 m to 0.11~0.28 m in horizontal and 2.85 m to 0.45 m in vertical accuracy, respectively. In addition, proposed data fusion approach of multi-sensing point cloud with the constraints of the height showed that the point matching error was greatly reduced under about 0.07 m. Accordingly, our proposed data fusion approach will enable us to generate effectively and timelinessly ortho-imagery and high-resolution three dimensional geographic data for national disaster management in the future.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.6
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• pp.663-670
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• 2020

In the present study, we assessed the accuracy of aerial triangulation using a UAV (Unmanned Aerial Vehicle) capable of network RTK (Real-Time Kinematic) survey in a disaster situation that may occur in a semi-urban area mixed with buildings. For a reliable survey of check points, they were installed on the roofs of buildings, and static GNSS (Global Navigation Satellite System) survey was conducted for more than four hours. For objective accuracy assessment, coded aerial targets were installed on the check points to be automatically recognized by software. At the instance of image acquisition, the 3D coordinates of the UAV camera were measured using VRS (Virtual Reference Station) method, as a kind of network RTK survey, and the 3-axial angles were achieved using IMU (Inertial Measurement Unit) and gimbal rotation measurement. As a result of estimation and update of the interior and exterior orientation parameters using Agisoft Metashape, the 3D RMSE (Root Mean Square Error) of aerial triangulation ranged from 0.153 m to 0.102 m according to the combination of the image overlap and the angle of the image acquisition. To get higher aerial triangulation accuracy, it was proved to be effective to incorporate oblique images, though it is common to increase the overlap of vertical images. Therefore, to conduct a UAV mapping in an urgent disaster site, it is necessary to acquire oblique images together rather than improving image overlap.

• Korean Journal of Remote Sensing
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• v.36 no.5_4
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• pp.1221-1229
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• 2020

In urgent situations such as disasters and accidents, rapid data acquisition and processing is required. Therefore, in this study, a rapid geocoding method according to EOP (Exterior Orientation Parameter) correction was proposed through pattern analysis of the initial UAV image information. As a result, in the research area with a total flight length of 1.3 km and a width of 0.102 ㎢, the generation time of geocoding images took about 5 to 10 seconds per image, showing a position error of about 8.51 m. It is believed that the use of the rapid geocoding method proposed in this study will help provide basic data for on-site monitoring and decision-making in emergency situations such as disasters and accidents.