• 한국측량학회:학술대회논문집
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• 한국측량학회 2010년 춘계학술발표회 논문집
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• pp.387-388
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• 2010

There is no generalized and systematic method yet to data pre-processing for point cloud data classification even if there have been lots of previous studies such as local maxima filter, morphology filter, slope based filter and so on. Main focus of this study is to present classification method for bare ground information from LiDAR data for the mountainous area.

• Journal of the Korean Data and Information Science Society
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• 제9권1호
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• pp.1-9
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• 1998

영과잉-포아송모형에서 변화시점이 있는 경우, 우도비 검정통계량을 이용하여 변화 시점의 유 무에 대한 가설을 검정하였다. 또한 적률 및 최우추정법을 이용하여 변화 시점과 몇가지 흥미있는 모수들을 추정하여 보았다. 이들 추정량을 비교하기 위하여 경험적인 평균제곱오차를 이용하였다. 변화시점이 있는 영과잉-포아송 모형과 변화시점이 없는 포아송 모형의 실례를 자료를 중심으로 설명하였다.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.215-223
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• 2021

3D data can be categorized into two parts : Euclidean data and non-Euclidean data. In general, 3D data exists in the form of non-Euclidean data. Due to irregularities in non-Euclidean data such as mesh and point cloud, early 3D deep learning studies transformed these data into regular forms of Euclidean data to utilize them. This approach, however, cannot use memory efficiently and causes loses of essential information on objects. Thus, various approaches that can directly apply deep learning architecture to non-Euclidean 3D data have emerged. In this survey, we introduce various deep learning methods for mesh and point cloud data. After analyzing the operating principles of these methods designed for irregular data, we compare the performance of existing methods for shape classification and segmentation tasks.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.345-346
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• 2023

As the shape and size of detectable objects diversifying recognition and segmentation algorithms have been developed to acquire accurate shape information. Although a high density of data captured by the repetition of scanning improves the accuracy of algorithms the high dense data decreases the efficiency due to its large size. This paper proposes standardization algorithms using the feature of structural members on indoor point cloud data to improve the process. First of all we determine the reduction rate of the density based on the features of the target objects then the data reduction algorithm compresses the data based on the reduction rate. Second the data arrangement algorithm rotates the data until the normal vector of data is aligned along the coordinate axis to allow the following algorithms to operate properly. Final the data arrangement algorithm separates the rotated data into their leaning axis. This allows reverse engineering of indoor point clouds to obtain the efficiency and accuracy of refinement processes.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제10권1호
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• pp.21-29
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• 2006

점 데이터로부터 곡선이나 곡면을 형성하는 방법은 널리 알려져 있다. 하지만 미분데이터가 주어지는 경우는 공학적으로 많지 않기 때문에 미분 데이터로부터 곡면을 형성하는 방법은 잘 사용되고 있지 않다. 여기서는 점 데이터, 1차 미분 데이터, 2차 미분 데이터 등 세 개중에 한 개 이상이 주어지면 곡면을 형성 할 수 있다. 1차 미분 데이터만 주어진 경우는 한 점에서 함수 값을 더한다. 2차 미분 데이터가 주어진 경우는 1차 함수를 추가하면 된다.

• 한국정밀공학회지
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• 제23권9호
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• pp.200-207
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• 2006

In this paper a new approach which combines implicit surface scheme and NURBS surface interpolation method is proposed in order to generate a complete surface model from unorganized point cloud data. In the method a base surface was generated by creating smooth implicit surface from the input point cloud data through which the actual surface would pass. The implicit surface was defined by a combination of shape functions including quadratic polynomial function, cubic polynomial functions and radial basis function using adaptive domain decomposition method. In this paper voxel data which can be extracted easily from the base implicit surface were used in order to generate rectangular net with good quality using the normal projection and smoothing scheme. After generating the interior points and tangential vectors in each rectangular region considering the required accuracy, the NURBS surface were constructed by interpolating the rectangular array of points using boundary tangential vectors which assure C$^1$ continuity between rectangular patches. The validity and effectiveness of this new approach was demonstrated by performing numerical experiments for the various types of point cloud data.

• 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.

• 국제학술발표논문집
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• The 8th International Conference on Construction Engineering and Project Management
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• pp.3-12
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• 2020

Nowadays, as-is BIM generation has been popularly adopted in the architecture, engineering, construction and facility management (AEC/FM) industries. In order to generate a 3D as-is BIM of a structural component, current methods require a registration process that merges different sets of point cloud data obtained from multiple locations, which is time-consuming and registration error-prone. To tackle this limitation, this study proposes a registration-free 3D point cloud data acquisition technique for as-is BIM generation. In this study, small-size mirrors that rotate in both horizontal and vertical direction are used to enable the registration-free data acquisition technique. First, a geometric model that defines the relationship among the mirrors, the laser scanner and the target component is developed. Second, determinations of optimal laser scanner location and mirror location are performed based on the developed geometrical model. To validate the proposed registration-free as-is BIM generation technique, simulation tests are conducted on key construction components including a PC slab and a structural wall. The result demonstrates that the registration-free point cloud data acquisition technique can be applicable in various construction elements including PC elements and structural components for as-is BIM generation.

• 제어로봇시스템학회논문지
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• 제9권9호
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• pp.714-719
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• 2003

We propose a measuring method of large object using the pattern matching. It is hard and expensive to get the complete 3D data when the object is large and exceeds the limit of measuring devices. The large object is divided into several smaller areas and is scanned several times to get the data of all the pieces. These data are aligned to get the complete 3D data using the pattern matching method such as point pattern matching method and transform matrix algorithm. The laser slit beam and CCD camera are applied for the experimental measurement. Visual C＋＋ on Windows 98 is implemented in processing the algorithm.

• International journal of advanced smart convergence
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• 제13권1호
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• pp.12-22
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• 2024

Software applications have a huge and inseparable impact on our lives. The complexity of the applications increases rapidly to support high performance and multifunction. Accordingly, the cost model for applications is increasingly important. Line of Code (LOC) and Man-Month (M/M) as the cost model measure the quantitative sides of the applications. Unlike them, Function Point (FP) measures the functionalities of the application. FP is efficient for estimating qualitative characteristics, but it is restricted to measuring the cost of an application using the wireless data broadcast which can support any number of clients. In this paper, we propose, a Function Point model for Information services using wireles data Broadcast (FPIB) to measure the development cost of an application that serves using the wireless data broadcast environment. FPIB adopts critical parameters of the wireless broadcast environment and the complexity of them to measure effectively the cost developing the application. Through the evaluation comparing the proposed FPIB with FP, we reveal the effectiveness of the proposed FPIB.