• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.3
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• pp.207-218
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• 2006

The extraction of horizontal alignment and cross-section of roads is very important task in road safety diagnosis. Existing road safety diagnosis methods by investigators need much time and expense but don't provide various data. Therefor, we need road shape classification automatically and extraction method of horizontal alignment and cross-section of roads through digital photogrammetry system using GPS-VAN with laser scanner. In this paper, we propose a method of mobile laser scanning data acquisition, processing and developing extraction methods of horizontal alignment and cross-section of roads using mobile laser scanning data by GPS-VAN.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.2
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• pp.111-122
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• 2015

This study purposed on introducing a new automated solution for detecting railway tracks and reconstructing track models from the mobile laser scanning data. The proposed solution completes following procedures; the study initiated with detecting a potential railway region, called Region Of Interest (ROI), and approximating the orientation of railway track trajectory with the raw data. At next, the knowledge-based detection of railway tracks was performed for localizing track candidates in the first strip. In here, a strip -referring the local track search region- is generated in the orthogonal direction to the orientation of track trajectory. Lastly, an initial track model generated over the candidate points, which were detected by GMM-EM (Gaussian Mixture Model-Expectation & Maximization) -based clustering strip- wisely grows to capture all track points of interest and thus converted into geometric track model in the tracking by detection framework. Therefore, the proposed railway track tracking process includes following key features; it is able to reduce the complexity in detecting track points by using a hypothetical track model. Also, it enhances the efficiency of track modeling process by simultaneously capturing track points and modeling tracks that resulted in the minimization of data processing time and cost. The proposed method was developed using the C++ program language and was evaluated by the LiDAR data, which was acquired from MMS over an urban railway track area with a complex railway scene as well.

• Korean Journal of Construction Engineering and Management
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• v.10 no.1
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• pp.136-145
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• 2009

The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.

• Journal of Korea Society of Industrial Information Systems
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• v.19 no.2
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• pp.85-91
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• 2014

The objective of the research is to automatically recognize railway objects from MLS data in which 9 key objects including terrain, track, bed, vegetation, platform, barrier, posts, attachments, powerlines are targeted. The proposed method can be divided into two main sub-steps. First, multi-scale contextual features are extracted to take the advantage of characterizing objects of interest from different geometric levels such as point, line, volumetric and vertical profile. Second, by considering contextual interactions amongst object labels, a contextual classifier is utilized to make a prediction with local coherence. In here, the Conditional Random Field (CRF) is used to incorporate the object context. By maximizing the object label agreement in the local neighborhood, CRF model could compensate the local inconsistency prediction resulting from other local classifiers. The performance of proposed method was evaluated based on the analysis of commission and omission error and shows promising results for the practical use.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.36 no.6
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• pp.443-449
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• 2018

Acquiring indoor point cloud, using SLAM (Simultaneous Localization and Mapping) based mobile mapping system, is an element progress for development of as-build BIM (Building Information Model) for the maintenance of the building. In this research we proposed a simulation-based target geometry determination for extrinsic calibration of multiple 2D laser scanning mobile system. Four different types of calibration sites were designed: (1) circle type; (2) rectangle type; (3) double circle type; and (4) double rectangle type. Based on the measurement values obtained from each simulated calibration site geometry, least squares solution based extrinsic calibration was derived. As a result, the rectangle type geometry is most suitable for extrinsic calibration of this system. Also, correlation values between extrinsic calibration parameters were high, and calibration results were distinct according to the calibration sites.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.6_1
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• pp.539-547
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• 2012

Volume survey for earthwork is conducted periodically at every month at large scaled construction sites for request payment for the construction. Currently, the earthwork volume is calculated on the overlapped drawing for two cross sections which were created by new and previous surveying data observed by GPS and TS. However the survey is required lots of time and expenses as it is a pin-point surveying method thus surveyors intend to get data only for the heavy undulated topographic features chosen by himself to save time and expenses. Consequently, it causes poor results due to low dense measurement as well as it's not matched with the results by another surveyors. As a result, the conflicts related in earthwork volume calculation often arises among the owner, contractors and sub contractors. In this study, we developed a method to get surveying data for fast and accurate volume calculation using 3D Mobile Laser System and conducted an application test. Also we carried out experiments for topographic survey using MLS to judge for the application additionally. The results showed that we could reduce a time for cross section survey from 48 hours to 2 hours and collected high dense data which have 0.2m interval instead of 3m interval compare with existing method. Also we could make a map which has high accuracy within 10cm in horizontal through topographic survey using MLS.