• Korean Journal of Remote Sensing
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• v.39 no.1
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• pp.111-127
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• 2023

In visual slam and 3D data modeling, the Iterative Closest Point method is a primary fundamental algorithm, and many technical fields have used this method. However, it relies on search methods that take a high search time. This paper solves this problem by applying an effective point cloud refinement method. And this paper also accelerates the point cloud registration process with an indexing scheme using the spatial decomposition method. Through some experiments, the results of this paper show that the proposed point cloud refinement method helped to produce better performance.

• Korean Journal of Computational Design and Engineering
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• v.10 no.3
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• pp.162-167
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• 2005

A 3D solid element mesh generation algorithm was newly developed. 3D surface points of global rectangular coordinates were supplied by a 3D laser scanner. The algorithm is strait forward and simple but it generates hexahedral solid elements. Then, the surface rectangular elements were generated from the solid elements. The key of the algorithm is elimination of unnecessary elements and 3D boundary surface fitting using given 3D surface point data.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.641-642
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• 2015

Unlike for other building processes, BIM for earthwork does not need a large variety of 3D model shapes; however, it requires a 3D model that can efficiently reflect the changing features of the ground shape and provide soil type-dependent workload calculation and information on equipment for optimal management. Objects for earthwork have not yet been defined because the current BIM system does not provide them. The BIM technology commonly applied in the manufacturing center uses real-object data obtained through 3D scanning to generate 3D parametric solid models. 3D scanning, which is used when there are no existing 3D models, has the advantage of being able to rapidly generate parametric solid models. In this study, A method to generate 3D models for earthwork operations using reverse engineering is suggested. 3D scanning is used to create a point cloud of a construction site and the point cloud data are used to generate a surface model, which was then converted into a parametric model with 3D objects for earthwork

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.5
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• pp.375-381
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• 2007

A novel method to register images onto 3D data, such as 3D point cloud, 3D vectors, and 3D surfaces, is proposed. The proposed method estimates the exterior orientation of a camera with respective to the 3D data though fitting pairs of the normal vectors of two planes passing a focal point and 2D and 3D lines extracted from an image and the 3D data, respectively. The fitting condition is that the angle between each pair of the normal vectors has to be zero. This condition can be represented as a numerical formula using the inner product of the normal vectors. This paper demonstrates the proposed method can estimate the exterior orientation for the image registration as simulation tests.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.113-118
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• 2010

Recently, 3D-reconstruction for geographic information and study of geospatial information is progressing in various fields through national policy such as R&D business and pilot project. LiDAR system has a advantage of acquisition the 3D information data easily and densely so that is used in many different fields. Considering to characterist of the point data formed with 3D, it need a high specification CPU because it requires a number of processing operation for 2D form expressed by monitor. In contrast, 2D grid structure, like DEM, has a advantage on costs because of simple structure and processing speed. Therefore, purpose of this study is to solve the problem of requirement of more storage space, when LiDAR data stored in forms of 3D is used for 3D-geographic and 3D-buliding representation. Additionally, This study reconstitutes 2D-gird data to supply the representation data of 3D-geographic and presents the storage method which is available for detailed representation applying tree-structure and reduces the storage space.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.30 no.1
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• pp.1-10
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• 2012

Recent spatial information technology has brought innovative improvement in both efficiency and accuracy. Especially, airborne LiDAR system(ALS) is one of the practical sensors to obtain 3D spatial information. Constructing reliable 3D spatial data infrastructure is world wide issue and most of the significant tasks involved with modeling manmade objects. This study aims to create a test data set for developing automatic building modeling methods by simulating point cloud data. The data simulates various roof types including gable, pyramid, dome, and combined polyhedron shapes. In this study, a robust bottom-up method to segment surface patches was proposed for generating building models automatically by determining model key points of the objects. The results show that building roofs composed of the segmented patches could be modeled by appropriate mathematical functions and the model key points. Thus, 3D digitizing man made objects could be automated for digital mapping purpose.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.9
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• pp.61-70
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• 2001

This paper introduces a new digitization method with sensor fusion for shape measurement in reverse engineering. Digitization can be classified into contact and non-contact type according to the measurement devices. Important thing in digitization is speed and accuracy. The former is excellent in speed and the latter is good for accuracy. Sensor fusion in digitization intends to incorporate the merits of both types so that the system can be automatized. Firstly, non-contact sensor with vision system acquires coarse 3D point data rapidly. This process is needed to identify and loco]ice the object located at unknown position on the table. Secondly, accurate 3D point data can be automatically obtained using scanning probe based on the previously measured coarse 3D point data. In the research, a great number of measuring points of equi-distance were instructed along the line acquired by the vision system. Finally, the digitized 3D point data are approximated to the rational B-spline surface equation, and the free-formed surface information can be transferred to a commercial CAD/CAM system via IGES translation in order to machine the modeled geometric shape.

• The Journal of Korea Robotics Society
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• v.11 no.3
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• pp.115-126
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• 2016

This paper suggests the method of the spherical signature description of 3D point clouds taken from the laser range scanner on the ground vehicle. Based on the spherical signature description of each point, the extractor of significant environmental features is learned by the Deep Belief Nets for the urban structure classification. Arbitrary point among the 3D point cloud can represents its signature in its sky surface by using several neighborhood points. The unit spherical surface centered on that point can be considered to accumulate the evidence of each angular tessellation. According to a kind of point area such as wall, ground, tree, car, and so on, the results of spherical signature description look so different each other. These data can be applied into the Deep Belief Nets, which is one of the Deep Neural Networks, for learning the environmental feature extractor. With this learned feature extractor, 3D points can be classified due to its urban structures well. Experimental results prove that the proposed method based on the spherical signature description and the Deep Belief Nets is suitable for the mobile robots in terms of the classification accuracy.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.680-681
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• 2015

This study develops an algorithm that automatically performs reverse engineering on three-dimensional (3D) sweeping shapes using a user's pre-defined feature templates and 3D point cloud data (PCD) of sweeping shapes. Existing methods extract 3D sweeping shapes by extracting points on a PCD cross section together with the center point in order to perform curve fitting and connect the center points. However, a drawback of existing methods is the difficulty of creating a 3D sweeping shape in which the user's preferred feature center points and parameters are applied. This study extracts shape features from cross-sectional points extracted automatically from the PCD and compared with pre-defined feature templates for similarities, thereby acquiring the most similar template cross-section. Fitting the most similar template cross-section to sweeping shape modeling makes the reverse engineering process automatic.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.495-507
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• 2023

The roughness of discontinuity significantly influences the mechanical characteristics of rock masses and extensively affects thermal and hydraulic behaviors. In this study, we utilized photogrammetry to generate 3D point cloud data for discontinuity and applied this data to characterize the roughness of discontinuity. The discontinuity profiles, reconstructed from the 3D point cloud data, were compared with those manually measured using a profile gauge. This comparison served to validate the accuracy and reliability of the acquired point cloud data in replicating the actual configurations of rock surfaces. Subsequent to this validation, influence of the number of profiles for representative JRC assessment was further investigated followed by suggestion of roughness anisotropy evaluation method with application of it to actual rock discontinuity surfaces.