• Spatial Information Research
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• v.19 no.4
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• pp.73-79
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• 2011

With the recent increase in demand for geo-registered imagery, Mobile Mapping Systems(MMS), which can quickly construct geographic information, has become important. The main part of MMS is the high-precision observation system, which collects geographic information at a certain speed. MMS has a complex data generation process and requires a standard-specific vehicle for its use, limiting its application range. In this paper, lightweight MMS is proposed to overcome its complexity by replacing the time synchronizer with a high-speed camera and by stabilizing motion with MEMS IMU/GPS. The proposed low-cost, portable method is expected to produce of geo-registered imagery efficiently.

• 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.

• Spatial Information Research
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• v.15 no.2
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• pp.169-180
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• 2007

Applicability of Land-based MMS(Mobile Mapping System) having been increased gradually as digitalization of administrative operation and construction of integrated systems of the government and provincial government are growing up. As these requirements, the case can be occurred that the facilities should be surveyed rapidly in the specific area. At this case, the real time field processing method is more necessary than the post processing method and data processing speed should be an essential element as important as accuracy. In this study, the two space intersection methods used in photogrammetry were programmed and compared with each other to select more proper method for the three dimensional positioning in the field processing. Especially, at the analytic space intersection, the traditional close range terrestrial photogrammetry was modified and applied to that to adapt to MMS's characteristics that camera position and attitude are changed according to the vehicle movement. As a result, the difference of the accuracy between two methods is not significant but at the calculation time, the analytic space intersection is faster three times than the space intersection using collinearity condition.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.3
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• pp.91-98
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• 2011

Road signs are part of the traffic facilities intended to guide drivers to their destinations in a safe and comfortable manner. Due to the creation of new routes, changes to the old routes, and the deterioration of road signs, road signs do require efforts to do ongoing field investigations and put the results in a database. The purpose of this study was to propose methodologies to do field investigations and build a database for road signs efficiently. For that purpose, a mobile mapping system was designed for field investigations. The designed mobile mapping system was comprised of three cameras to produce image information about road signs, GPS/IMU/DMI to obtain information about the position and attitude of a vehicle, and a laser scanner to generate information about the locations of road signs and routes. Also proposed in the study was a procedure to automatically detect the areas of road signs in the road signs images and recognize their characters.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.48 no.1
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• pp.55-60
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• 2011

The most basic algorithm in SLAM(Simultaneous Localization And Mapping) technique of mobile robots is EKF(Extended Kalman Filter) SLAM. However, it requires prior information of characteristics of the system and the noise model which cannot be estimated in accurate. By this limit, Kalman Filter shows the following behaviors in a highly uncertain environment: becomes too sensitive to internal parameters, mathematical consistency is not kept, or yields a wrong estimation result. In contrast, $H_{\infty}$ filter does not requires a prior information in detail. Thus, based on a idea that $H_{\infty}$ filter based SLAM will be more robust than the EKF-SLAM, we propose a framework of $H_{\infty}$ filter based SLAM and show that suggested algorithm shows slightly better result man me EKF-SLAM in a highly uncertain environment.

• 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.

• 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 Korea Spatial Information System Society
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• v.4 no.2 s.8
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• pp.55-64
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• 2002

VEfficient generation of road data is one of the most important issues in GIS (Geographic Information System). In this paper, we propose a hybrid approach for automatic generation of road data by combining mobile mapping and image processing techniques. Mobile mapping systems have a form of vehicle equipped with CCD camera, GPS, and INS. They can calculate absolute position of objects that appear in acquired image by photogrammetry, but it is labor-intensive and time-consuming. Automatic road detection methods have been studied also by image processing technology. However, the methods are likely to fail because of obstacles and exceptive conditions in the real world. To overcome the problems, we suggest a hybrid method for automatic road generation, by exploiting both GPS/INS data acquired by mobile mapping system and image processing algorithms. We design an estimator to estimate 3-D coordinates of road line and corresponding location in an image. The estimation process reduces complicated image processing operations that find road line. The missing coordinates of road line due to failure of estimation are obtained by cubic spline interpolation. The interpolation is done piecewise, separated by rapid change such as road intersection. We present experimental results of the suggested estimation and interpolation methods with image sequences acquired by mobile mapping system, and show that the methods are effective in generation of road data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.4
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• pp.536-543
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• 2017

This study developed a new methodology to evaluate the carbon storage using a Mobile Mapping System according to the life cycle of street trees. The system for calculating the carbon storage of a roadside tree using the MMS developed in this study consisted of a database, memory, processor, user interface, and communication module. The carbon storage was calculated for 261 trees in the Cheonan-Asan New Town (distance: 2.1 km, area: $283,698m^2$). The average biomass and carbon storage of Metasequoia glyptostroboides were highest at 34.5 kg and 17.3 kg C and Chionanthus retusa were lowest at 19.5 kg and 9.8 kg C, respectively. The total biomass and total carbon storage of Ginkgo biloba were highest at 5028.8 kg and 17.3 kg C and Chionanthus retusa were lowest at 780.7 kg and 390.3 kg C, respectively. Based on the roadside tree database, the amount of carbon storage in a given area was converted to Google format and visualized in 3D by GIS analysis.

• Journal of the Korean Association of Geographic Information Studies
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• v.22 no.3
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• pp.99-106
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• 2019

Technology that cannot be excluded from 4th industry is self-driving sector. The self-driving sector can be seen as a key set of technologies in the fourth industry, especially in the DB sector is getting more and more popular as a business. The DB, which was previously produced and managed in two dimensions, is now evolving into three dimensions. Among the data obtained by Mobile Mapping System () to produce the HD MAP necessary for self-driving, Point Cloud, which is LiDAR data, is used as a DB because it contains accurate location information. However, at present, it is not widely used as a base data for 3D modeling in addition to HD MAP production. In this study, MMS Point Cloud was used to extract facilities around the road and to overlay the location to expand the usability of Point Cloud. Building utility poles and communication poles DB from Point Cloud and comparing road name address base and location, it is believed that the accuracy of the location of the facility DB extracted from Point Cloud is also higher than the basic road name address of the road, It is necessary to study the expansion of the facility field sufficiently.