• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.26 no.1
• /
• pp.73-83
• /
• 2008

For spatial analysis and decision-making based on territorial and urban information, technologies on 3D GIS with digital image data and photo-realistic 3D image models to visualize 3D modeling are being rapidly developed. Currently, satellite images, aerial images and aerial LiDAR data are mostly used to build 3D models and textures from oblique aerial photographs or terrestrial photographs are used to create 3D image models. However, we are in need of quality 3D image models as current models cannot express topographic and features most elaborately and realistically. Thus, this study analyzed techniques to use aerial photographs, aerial LiDAR, terrestrial photographs and terrestrial LiDAR to create a 3D image model with artificial features and special topographic that emphasize spatial accuracy, delicate depiction and photo-realistic imaging. A 3D image model with spatial accuracy and photographic texture was built to be served via 3D image map services systems on the Internet. As it was necessary to consider intended use and display scale when building 3D image models, in this study, we applied the concept of LoD(Level of Detail) to define 3D image model of buildings in five levels and established the models by following the levels.

• Tunnel and Underground Space
• /
• v.33 no.3
• /
• pp.126-140
• /
• 2023

In this study, the cause of subsidence in limestone mine was analyzed using a LiDAR-based geometry model. Using UAV and ground-based LiDAR systems, a precise geometry model was constructed for the subsidence surface and mine tunnel, and the results of on-site geological survey and rock mass classification were utilized. Through the geometry model, distribution of thickness of crown pillar and faults around the subsidence area, calculation of the volume of the subsidence area and subsidence deposit, and analysis of the subsidence surface inclination were conducted. Through these analyzes, the causes of ground subsidence were identified.

• Journal of Aerospace System Engineering
• /
• v.15 no.1
• /
• pp.102-110
• /
• 2021

Recently, multi-copters equipped with various collision avoidance sensors have been introduced to improve flight stability. LiDAR is used to recognize a three-dimensional position. Multiple cameras and real-time SLAM technology are also used to calculate the relative position to obstacles. A three-dimensional depth sensor with a small process and camera is also used. In this study, a small collision-avoidance multi-copter system capable of in-door flight was developed as a platform for the development of collision avoidance software technology. The multi-copter system was equipped with LiDAR, 3D depth sensor, and small image processing board. Object recognition and collision avoidance functions based on the YOLO algorithm were verified through flight tests. This paper deals with recent trends in drone collision avoidance technology, system design/manufacturing process, and flight test results.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.18 no.5
• /
• pp.203-208
• /
• 2023

Recently, with the growing interest in the field of autonomous driving, many researchers have been focusing on developing autonomous driving software platforms. In particular, we have concentrated on developing 3D object detection models that can improve real-time performance. In this paper, we introduce a self-constructed 3D LiDAR dataset specific to domestic environments and propose a VariFocal-based CenterPoint for the 3D object detection model, with improved performance over the previous models. Furthermore, we present experimental results comparing the performance of the 3D object detection modules using our self-built and public dataset. As the results show, our model, which was trained on a large amount of self-constructed dataset, successfully solves the issue of failing to detect large vehicles and small objects such as motorcycles and pedestrians, which the previous models had difficulty detecting. Consequently, the proposed model shows a performance improvement of about 1.0 mAP over the previous model.

• Journal of the Speleological Society of Korea
• /
• no.90
• /
• pp.35-56
• /
• 2009

The purpose of this paper is to analyze the implementation of the karst infrastructure systems for the u-cave. IT based u-cave represents spatial information derived fields, such as geographical distribution of the cave boundaries, physical configuration of the cave locations and formation characteristics of the karst history. These three aspects relate to karst infrastructure systems, cave monitoring center and spatial database implementation. In terms of the IT based u-cave infrastructure implementation systems, the u-cave depends on IT contents and spatial features. uIT contents are strongly related to IT839 strategy due to the national agenda is "u-Korea". Cave should contribute to u-cave construction through the spatial analyses methods including USN, RFID, LiDAR, ELD, and GIS technologies. For these methods various cave functions will guide to u-cave's distribution, location, and characteristics of karst. The infrastructure consists of landforms and speleothem facilities, underground related facilities, environmental protection systems, and cave planning. These six units of the cave infrastructures have spatial databases that consist of spatial configuration, such as 4-D in order to draw the spatial distribution of the limestone and lava caves. IT based u-cave system infrastructure implementation should deal with IT convergence to generate fusion affects.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.3
• /
• pp.312-320
• /
• 2020

3D scanning began in the field of manufacturing. In the construction field, a BIM (Building Information Modeling)-based 3D modeling environment was developed and used for the overall construction, such as factory prefabrication, structure construction inspection, plant facility, bridge, tunnel structure inspection using 3D scanning technology. LiDARs have higher accuracy and density than mobile scanners but require longer registration times and data processing. On the other hand, in interior building space management, relatively high accuracy is not needed, and the user can conveniently move with a mobile scan system. This study derives considerations for the development of Simultaneous Localization and Mapping (SLAM)-based Scan Backpack systems that move freely and support real-time point cloud registration. This paper proposes the mobile scan system, framework, and component structure to derive the considerations and improve scan productivity. Prototype development was carried out in two stages, SLAM and ScanBackpack, to derive the considerations and analyze the results.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.28 no.1
• /
• pp.133-142
• /
• 2010

To monitor composition and change of the national land, intelligent topographical classifier which enables accurate classification of land-cover types from airborne LiDAR data is highly required. We developed a topographical classifier development support system cooperating with da1a mining tool WEKA to help users to construct accurate topographical classification systems. The topographical classifier development support system has the following functions; superposing LiDAR data upon corresponding aerial images, dividing LiDAR data into tiles for efficient processing, 3D visualization of partial LiDAR data, feature from tiles, automatic WEKA input generation, and automatic C++ program generation from the classification rule set. In addition, with dam mining tool WEKA, we can choose highly distinguishable features by attribute selection function and choose the best classification model as the result topographical classifier. Therefore, users can easily develop intelligent topographical classifier which is well fitted to the developing objectives by using the topographical classifier development support system.

• KIPS Transactions on Computer and Communication Systems
• /
• v.3 no.8
• /
• pp.251-260
• /
• 2014

3D point data is utilized in various industry domains for its high accuracy to the surface information of an object. It is substantially utilized in geography for terrain scanning and analysis. Generally, 3D point data need to be changed by Gridding which produces a regularly spaced array of z values from irregularly spaced xyz data. But it requires long processing time and high resource cost to interpolate grid coordination. Kriging interpolation in Gridding has attracted because Kriging interpolation has more accuracy than other methods. However it haven't been used frequently since a processing is complex and slow. In this paper, we presented a parallel Gridding algorithm which contains Kriging and an application of grid data structure to fit MapReduce paradigm to this algorithm. Experiment was conducted for 1.6 and 4.3 billions of points from Airborne LiDAR files using our proposed MapReduce structure and the results show that the total execution time is decreased more than three times to the convention sequential program on three heterogenous clusters.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.1
• /
• pp.33-40
• /
• 2022

With the recent increase in the development of military drones, they are adopted and used as the combat system of battalion level or higher. However, it is difficult to use drones that can be used in battles below the platoon level due to the current conditions for the formation of units in the Korean military. In this paper, therefore, we developed a program drones equipped with a thermal imaging camera and LiDAR sensor for reconnaissance and exploration that can be applied in battles below the platoon level. Using these drones, we studied the possibility and feasibility of drones for small-scale combats that can find hidden enemies, search for an appropriate detour through image processing and conduct reconnaissance and search for battlefields, hiding and cover-up through image processing. In addition to the purpose of using the proposed drone to search for an enemies lying in ambush in the battlefield, it can be used as a function to check the optimal movement path when a combat unit is moving, or as a function to check the optimal place for cover-up or hiding. In particular, it is possible to check another route other than the route recommended by the program because the features of the terrain can be checked from various viewpoints through 3D modeling. We verified the possiblity of flying by designing and assembling in a form of adding LiDAR and thermal imaging camera module to a drone assembled based on racing drone parts, which are open source hardware, and developed autonomous flight and search functions which can be used even by non-professional drone operators based on open source software, and then installed them to verify their feasibility.

• Journal of Information Processing Systems
• /
• v.14 no.6
• /
• pp.1445-1456
• /
• 2018

Environment perception and three-dimensional (3D) reconstruction tasks are used to provide unmanned ground vehicle (UGV) with driving awareness interfaces. The speed of obstacle segmentation and surrounding terrain reconstruction crucially influences decision making in UGVs. To increase the processing speed of environment information analysis, we develop a CPU-GPU hybrid system of automatic environment perception and 3D terrain reconstruction based on the integration of multiple sensors. The system consists of three functional modules, namely, multi-sensor data collection and pre-processing, environment perception, and 3D reconstruction. To integrate individual datasets collected from different sensors, the pre-processing function registers the sensed LiDAR (light detection and ranging) point clouds, video sequences, and motion information into a global terrain model after filtering redundant and noise data according to the redundancy removal principle. In the environment perception module, the registered discrete points are clustered into ground surface and individual objects by using a ground segmentation method and a connected component labeling algorithm. The estimated ground surface and non-ground objects indicate the terrain to be traversed and obstacles in the environment, thus creating driving awareness. The 3D reconstruction module calibrates the projection matrix between the mounted LiDAR and cameras to map the local point clouds onto the captured video images. Texture meshes and color particle models are used to reconstruct the ground surface and objects of the 3D terrain model, respectively. To accelerate the proposed system, we apply the GPU parallel computation method to implement the applied computer graphics and image processing algorithms in parallel.