• 한국측량학회지
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• 제25권6_1호
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• pp.507-516
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• 2007

Segmentation and organization of the LiDAR (Light Detection and Ranging) data of the Earth's surface are difficult tasks because the captured LiDAR data are composed of irregularly distributed point clouds with lack of semantic information. The reason for this difficulty in processing LiDAR data is that the data provide huge amount of the spatial coordinates without topological and/or relational information among the points. This study introduces LiDAR data segmentation technique by utilizing histograms of the LiDAR height image data and analyzing roof shape for 3D reconstruction and visualization of the buildings. One of the advantages in utilizing LiDAR height image data is no registration required because the LiDAR data are geo-referenced and ortho-projected data. In consequence, measurements on the image provide absolute reference coordinates. The LiDAR image allows measurement of the initial building boundaries to estimate locations of the side walls and to form the planar surfaces which represent approximate building footprints. LiDAR points close to each side wall were grouped together then the least-square planar surface fitting with the segmented point clouds was performed to determine precise location of each wall of an building. Finally, roof shape analysis was performed by accumulated slopes along the profiles of the roof top. However, simulated LiDAR data were used for analyzing roof shape because buildings with various shapes of the roof do not exist in the test area. The proposed approach has been tested on the heavily built-up urban residential area. 3D digital vector map produced by digitizing complied aerial photographs was used to evaluate accuracy of the results. Experimental results show efficiency of the proposed methodology for 3D building reconstruction and large scale digital mapping especially for the urban area.

• Journal of Information Processing Systems
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• 제12권3호
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• pp.338-357
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• 2016

The recent advent of increasingly affordable and powerful 3D scanning devices capable of capturing high resolution range data about real-world objects and environments has fueled research into effective 3D surface reconstruction techniques for rendering the raw point cloud data produced by many of these devices into a form that would make it usable in a variety of application domains. This paper, therefore, provides an overview of the existing literature on surface reconstruction from 3D point clouds. It explains some of the basic surface reconstruction concepts, describes the various factors used to evaluate surface reconstruction methods, highlights some commonly encountered issues in dealing with the raw 3D point cloud data and delineates the tradeoffs between data resolution/accuracy and processing speed. It also categorizes the various techniques for this task and briefly analyzes their empirical evaluation results demarcating their advantages and disadvantages. The paper concludes with a cross-comparison of methods which have been evaluated on the same benchmark data sets along with a discussion of the overall trends reported in the literature. The objective is to provide an overview of the state of the art on surface reconstruction from point cloud data in order to facilitate and inspire further research in this area.

• 한국CDE학회논문집
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• 제11권5호
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• pp.335-343
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• 2006

Design changes for an original surface model are frequently required in a manufacturing area: for example, when the physical parts are modified or when the parts are partially manufactured from analogous shapes. In this case, an efficient 3D model updating method by locally adding scan data for the modified area is highly desirable. For this purpose, this paper presents a new procedure to update an initial model that is composed of combinatorial triangular facets based on a set of locally added point data. The initial surface model is first created from the initial point set by Tight Cocone, which is a water-tight surface reconstructor; and then the point cloud data for the updates is locally added onto the initial model maintaining the same coordinate system. In order to update the initial model, the special region on the initial surface that needs to be updated is recognized through the detection of the overlapping area between the initial model and the boundary of the newly added point cloud. After that, the initial surface model is eventually updated to the final output by replacing the recognized region with the newly added point cloud. The proposed method has been implemented and tested with several examples. This algorithm will be practically useful to modify the surface model with physical part changes and free-form surface design.

• Advances in Computational Design
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• 제3권4호
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• pp.319-338
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• 2018

High-performing architecture should be designed by taking into account the mutual dependency between the new building and the local context. The performative architecture plays an important role to avert any unforeseen failures after the building has been built; particularly ones related to the microclimate impacts that affect the human comfort. The use of the concept of solar envelopes helps designers to construct the developable mass of the building design considering the solar access and the site obstruction. However, the current analysis method using solar envelopes lack in terms of integrating the detailed information of the existing context during the simulation process. In architectural design, often the current site modelling not only absent in preserving the complex geometry but also information on the surface characteristics. Currently, the emerging applications of point clouds offer a great possibility to overcome these limitations, since they include the attribute information such as XYZ as the position information and RGB as the color information. This study particularly presents a comparative analysis between the manually built 3D models and the models generated from the point cloud data. The modelling comparisons focus on the relevant factors of solar radiation and a set of simulation to calculate the performance indicators regarding selected portions of the models. The experimental results emphasize an introduction of the design approach and the dataset visibility of the 3D existing environments. This paper ultimately aims at improving the current architectural decision of support environment means, by increasing the correspondence between the digital models for performance analysis and the real environments (context of design) during the conceptual design phase.

• 대한기계학회논문집A
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• 제26권10호
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• pp.1961-1970
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• 2002

A laser scanner is widely used fur a device fur acquiring point data in reverse engineering. It is more efficient to generate a surface automatically from the line-typed data than scattered data of points clouds. In the case of a compound model, it is hard to represent all the scanned data into one surface maintaining its original line characteristics. In this paper, a method is presented to generate a surface by the segmentation of measured point data. After forming triangular net, the segmentation is done by the user input such as the angle between triangles, the number of facets to be considered as small segment, and the angle for combining small segment. B-spline fitting is implemented to the point data in each segment. The surface generation through segmentation shows a reliable result when it is applied to the models with curvature deviation regions. An useful algorithm for surface reconstruction is developed and verified by applying an practical model and shows a good tools fur reverse engineering in design modification.

• 천문학논총
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• 제30권2호
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• pp.283-287
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• 2015

Within the context of the hugely successful SAGE-LMC and SAGE-SMC surveys, Spitzer photometry observations of the Large and Small Magellanic Clouds have revealed millions of infrared point sources in each galaxy. The brightest infrared sources are generally dust producing and mass-losing evolved stars, and several tens of thousands of such stars have been classified. After photometrically classifying these objects, the dust production by several kinds of evolved stars - such as Asymptotic Giant Branch stars and Red Supergiants - can be determined. SAGE-Spec is the spectroscopic follow-up to the SAGE-LMC survey, and it has obtained Spitzer-IRS $5-40{\mu}m$ spectroscopy of about 200 sources in the LMC. Combined with archival data from other programs, observations at a total of ~1000 pointings have been obtained in the LMC, while ~250 IRS pointings were observed in the SMC. Of these, a few hundred pointings represent dust producing and mass-losing evolved stars, covering a range in colors, luminosities, and thus mass-loss rates. Red Supergiants and O-rich and C-rich AGB stars - the main dust producers - are well represented in the spectroscopic sample. This paper will summarize what we know about the mineralogy of dust producing evolved stars, and discuss their relative importance in the total dust budget.

• 한국CDE학회논문집
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• 제14권1호
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• pp.10-17
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• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.783-786
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• 2021

In recent years, the use of LiDAR sensors is increasing as autonomous driving, robot control, and drones are considered more. Contrary to ordinary cameras, LiDAR sensors make it possible to handle challenging problems by calculating the distance between objects. This crucial characteristic makes more active research on deep learning models dealing with point clouds which are data of LiDAR. In this paper, among the schemes of using the point cloud, the Point-based approach is mainly discussed. Furthermore, future streams and insights can be considered by looking at solving methods and the limitations.

• 한국측량학회지
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• 제26권5호
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• pp.485-491
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• 2008

LiDAR systems are usually incorporated a laser scanner and GPS/INS modules with a digital aerial camera. LiDAR point clouds and digital aerial images acquired by the systems provide complementary spatial information on the ground. In addition, some of laser scanners provide intensity, radiometric information on the surface of the earth. Since the intensity is unnecessary of registration and provides the radiometric information at a certain wavelength on the location of LiDAR point, it can be a valuable ancillary information but it does not deliver sufficient radiometric information compared with digital images. This study utilize the LiDAR points as ground control points (GCPs) to adjust exterior orientations(EOs) of the stereo images. It is difficult to find exact point of LiDAR corresponding to conjugate points in stereo images, but this study used intensity of LiDAR as an ancillary data to find the GCPs. The LiDAR points were successfully used to adjust EOs of stereo aerial images, therefore, successfully provided the prerequisite for the precise registration of the two data sets from the LiDAR systems.

• ETRI Journal
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• 제39권2호
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• pp.181-190
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• 2017

The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.