• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.3
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• pp.243-251
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• 2016

LiDAR data processing steps include noise removal, filtering, classification, segmentation, shape recognition, modeling, and quality assessment. This paper focuses on modeling and accuracy evaluation of 3D objects with curved surfaces. The appropriate modeling functions were determined by analyzing surface patch shape. Existing methods for modeling curved surface features require linearization, initial approximation, and iteration of the non-linear functions. However, proposed method could directly estimate the unknown parameters of the modeling functions. The results demonstrate feasibility of the proposed method. The proposed method was applied to the simulated and real building data of hemi-spherical and semi-cylindrical surfaces. The parameters and accuracy of the modeling functions were estimated. It is expected that the proposed method would contribute to automatic modeling of various objects.

• Journal of the Korean Institute of Landscape Architecture
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• v.44 no.1
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• pp.93-106
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• 2016

This study aimed to estimate and evaluate the thermal mitigation of the urban tree canopy on the summer outdoor environment by quantitative use of mean radiant temperature. This study applied the SOLWEIG model based $T_{mrt}$ comparison method by using both (1) urban tree canopy presence examples and (2) urban tree canopy absence examples as constructed from airborne LiDAR system based three-dimensional point cloud data. As a result, it was found that an urban tree canopy can provide a decrease in the entire domain averaged daily mean $T_{mrt}$ about $5^{\circ}C$ and that the difference can increase up to $33^{\circ}C$ depending both on sun position and site conditions. These results will enhance urban microclimate studies such as indices (e.g., wind speed, humidity, air temperature) and biometeorology (e.g., perceived temperature) and will be used to support forest based public green policy development.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.81-87
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• 2016

It is important to analyze the exact damage information for fast recovery when natural disasters cause damage on river-side facilities such as dams, bridges, embankments etc. In this study, we shows the method to effectively damage analysis plan using UAV(Unmanned aerial vehicle) images and accuracy assessment of it. The UAV images are captured on area near the river-side facilities and the core methodology for damage analysis are image matching and change detection algorithm. The result(point cloud) from image matching is to construct 3-dimensional data using by 2-dimensional images, it extracts damage areas by comparing the height values on same area with reference data. The results are tested absolute locational precision compared by post-processed aerial LiDAR data named reference data. The assessment analysis test shows our matching results 10-20 centimeter level precision if external orientation parameters are very accurate. This study shows suggested method is very useful for damage analysis in a large size structure like river-side facilities. But the complexity building can't apply this method, it need to the other method for damage analysis.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.29 no.5
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• pp.459-469
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• 2011

There are various factors for determining object shape, such as size, slope and its direction, curvature, length, surface, angles between lines or planes, distribution of the model key points, and so on. Most of the object description and recognition methods are for the 2D space not for the 3D object space where the objects actually exist. In this study, 3D chain code operator, which is basically extension of 2D chain code, was proposed for object description and analysis in 3D space. Results show that the sequence of the 3D chain codes could be basis of a top-down approach for object recognition and modeling. In addition, the proposed method could be applicable to segment point cloud data such as LiDAR data.

• 전자공학회논문지 IE
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• v.46 no.1
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• pp.7-15
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• 2009

In this paper, automatic structure boundary extraction is proposed using terrestrial LIDAR (Light Detection And Ranging) in 3-dimensional data. This paper describes an algorithm which does not use pictures and pre-processing. In this algorithm, an efficient decimation method is proposed, considering the size of object, the amount of LIDAR data, etc. From these decimated data, object points and non-object points are distinguished using distance information which is a major features of LIDAR. After that, large and small values are extracted using local variations, which can be candidate for boundary. Finally, a boundary line is drawn based on the boundary point candidates. In this way, the approximate boundary of the object is extracted.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.4
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• pp.383-390
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• 2020

Car-mounted MMS (Mobile Mapping System) is the most effective tool for mapping of high definition road maps(HD Map). The MMS is composed of various sensor combinations, and the manufacturing methods and processing software are different for each manufacturer, performance cannot be predicted only by the specifications of the parts. Therefore, it is necessary to judge whether each equipment is suitable for mapping through performance evaluation, and facilities for periodic performance evaluation. In this paper, we explained the MMS performance evaluation facilities built at the SOC Evaluation Research Center of Korea Institute of Civil Engineering and Building Technology and analyzed the conditions that the evaluation facilities should have through a literature survey and field tests.

• Computers and Concrete
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• v.33 no.5
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• pp.595-603
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• 2024

In the construction industry, there has been a surge in the implementation of high-tech equipment in recent years. Various technologies are being considered as potential solutions for future construction projects. Building information modeling (BIM), which utilizes advanced equipment, is a promising solution among these technologies. The need for safety inspection has also increased with the aging structures. Nevertheless, traditional safety inspection technology falls short of meeting this demand as it heavily relies on the subjective opinions of workers. This inadequacy highlights the need for advancements in existing maintenance technology. Research on building safety inspection using 3D laser scanners has notably increased. Laser scanners that use light detection and ranging (LiDAR) can quickly and accurately acquire producing information, which can be realized through reverse engineering by modeling point cloud data. This study introduces an innovative evaluation system for building safety using a 3D laser scanner. The system was used to assess the safety of an existing three-story building by implementing a reverse engineering technique. The 3D digital data are obtained from the scanner to detect defects and deflections in and outside the building and to create an as-built BIM. Subsequently, the as-built structural model of the building was generated using the reverse engineering approach and used for structural analysis. The acquired information, including deformations and dimensions, is compared with the expected values to evaluate the effectiveness of the proposed technique.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.481-486
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• 2014

This study aims at enhancing the performance of file-referring octree, suggested by Han(2014), for efficiently querying huge 3D point clouds, acquired by the 3D terrestrial laser scanning. Han's method(2014) has revealed a problem of heavy declining in query speed, when if it was applied on a very long tunnel, which is the lengthy and narrow shaped anisometric structure. Hereupon, the shape of octree has been analyzed of its influence on the query efficiency with the testing method of generating an independent octree in each isometric subdivision of 3D object boundary. This method tested query speed and main memory usage against the conventional single octree method by capturing about 300 million points in a very long tunnel. Finally, the testing method resulted in which twice faster query speed is taking similar size of memory. It is also approved that the conclusive factor influencing the query speed is the destination level, but the query speed can still increase with more proximity to isometric bounding shape of octree. While an excessive unbalance of octree shape along each axis can heavily degrade the query speed, the improvement of octree shape can be more effectively enhancing the query speed than increasement of destination level.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1125-1139
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• 2022

In an unmanned aerial vehicles (UAVs) system, a physical offset can be existed between the global positioning system/inertial measurement unit (GPS/IMU) sensor and the observation sensor such as a hyperspectral sensor, and a lidar sensor. As a result of the physical offset, a misalignment between each image can be occurred along with a flight direction. In particular, in a case of multi-sensor system, an observation sensor has to be replaced regularly to equip another observation sensor, and then, a high cost should be paid to acquire a calibration parameter. In this study, we establish a precise sensor model equation to apply for a multiple sensor in common and propose an independent physical offset estimation method. The proposed method consists of 3 steps. Firstly, we define an appropriate rotation matrix for our system, and an initial sensor model equation for direct-georeferencing. Next, an observation equation for the physical offset estimation is established by extracting a corresponding point between a ground control point and the observed data from a sensor. Finally, the physical offset is estimated based on the observed data, and the precise sensor model equation is established by applying the estimated parameters to the initial sensor model equation. 4 region's datasets(Jeon-ju, Incheon, Alaska, Norway) with a different latitude, longitude were compared to analyze the effects of the calibration parameter. We confirmed that a misalignment between images were adjusted after applying for the physical offset in the sensor model equation. An absolute position accuracy was analyzed in the Incheon dataset, compared to a ground control point. For the hyperspectral image, root mean square error (RMSE) for X, Y direction was calculated for 0.12 m, and for the point cloud, RMSE was calculated for 0.03 m. Furthermore, a relative position accuracy for a specific point between the adjusted point cloud and the hyperspectral images were also analyzed for 0.07 m, so we confirmed that a precise data mapping is available for an observation without a ground control point through the proposed estimation method, and we also confirmed a possibility of multi-sensor fusion. From this study, we expect that a flexible multi-sensor platform system can be operated through the independent parameter estimation method with an economic cost saving.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.1
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• pp.174-192
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• 2021

The LIDAR sensor, which provides higher cognitive performance than cameras and radar, is difficult to apply to ADAS or autonomous driving because of its high price. On the other hand, as the price is decreasing rapidly, expectations are rising to improve existing autonomous driving functions by taking advantage of the LIDAR sensor. In level 3 autonomous vehicles, when a dangerous situation in the cognitive module occurs due to a sensor defect or sensor limit, the driver must take control of the vehicle for manual driving. If the driver does not respond to the request, the system must automatically kick in and implement a minimum risk maneuver to maintain the risk within a tolerable level. In this study, based on this background, a LIDAR-based LKS MRM algorithm was developed for the case when the normal operation of LKS was not possible due to troubles in the cognitive system. From point cloud data collected by LIDAR, the algorithm generates the trajectory of the vehicle in front through object clustering and converts it to the target waypoints of its own. Hence, if the camera-based LKS is not operating normally, LIDAR-based path tracking control is performed as MRM. The HAZOP method was used to identify the risk sources in the LKS cognitive systems. B, and based on this, test scenarios were derived and used in the validation process by simulation. The simulation results indicated that the LIDAR-based LKS MRM algorithm of this study prevents lane departure in dangerous situations caused by various problems or difficulties in the LKS cognitive systems and could prevent possible traffic accidents.