• Title/Summary/Keyword: Point data

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Extraction of Geometric Primitives from Point Cloud Data

  • Kim, Sung-Il;Ahn, Sung-Joon
    • 제어로봇시스템학회:학술대회논문집
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    • 2005.06a
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    • pp.2010-2014
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    • 2005
  • Object detection and parameter estimation in point cloud data is a relevant subject to robotics, reverse engineering, computer vision, and sport mechanics. In this paper a software is presented for fully-automatic object 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. The 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. Curvature analysis of the local quadric surfaces fitted to small patches of point cloud provides the necessary seed information for automatic model selection, point segmentation, and model fitting. The performance of the software on a variety of point cloud data will be demonstrated live.

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Analysis of overlap ratio for registration accuracy improvement of 3D point cloud data at construction sites (건설현장 3차원 점군 데이터 정합 정확성 향상을 위한 중첩비율 분석)

  • Park, Su-Yeul;Kim, Seok
    • Journal of KIBIM
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    • v.11 no.4
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    • pp.1-9
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    • 2021
  • Comparing to general scanning data, the 3D digital map for large construction sites and complex buildings consists of millions of points. The large construction site needs to be scanned multiple times by drone photogrammetry or terrestrial laser scanner (TLS) survey. The scanned point cloud data are required to be registrated with high resolution and high point density. Unlike the registration of 2D data, the matrix of translation and rotation are used for registration of 3D point cloud data. Archiving high accuracy with 3D point cloud data is not easy due to 3D Cartesian coordinate system. Therefore, in this study, iterative closest point (ICP) registration method for improve accuracy of 3D digital map was employed by different overlap ratio on 3D digital maps. This study conducted the accuracy test using different overlap ratios of two digital maps from 10% to 100%. The results of the accuracy test presented the optimal overlap ratios for an ICP registration method on digital maps.

Accuracy Evaluation by Point Cloud Data Registration Method (점군데이터 정합 방법에 따른 정확도 평가)

  • Park, Joon Kyu;Um, Dae Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.1
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    • pp.35-41
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    • 2020
  • 3D laser scanners are an effective way to quickly acquire a large amount of data about an object. Recently, it is used in various fields such as surveying, displacement measurement, 3D data generation of objects, construction of indoor spatial information, and BIM(Building Information Model). In order to utilize the point cloud data acquired through the 3D laser scanner, it is necessary to make the data acquired from many stations through a matching process into one data with a unified coordinate system. However, analytical researches on the accuracy of point cloud data according to the registration method are insufficient. In this study, we tried to analyze the accuracy of registration method of point cloud data acquired through 3D laser scanner. The point cloud data of the study area was acquired by 3D laser scanner, the point cloud data was registered by the ICP(Iterative Closest Point) method and the shape registration method through the data processing, and the accuracy was analyzed by comparing with the total station survey results. As a result of the accuracy evaluation, the ICP and the shape registration method showed 0.002m~0.005m and 0.002m~0.009m difference with the total station performance, respectively, and each registration method showed a deviation of less than 0.01m. Each registration method showed less than 0.01m of variation in the experimental results, which satisfies the 1: 1,000 digital accuracy and it is suggested that the registration of point cloud data using ICP and shape matching can be utilized for constructing spatial information. In the future, matching of point cloud data by shape registration method will contribute to productivity improvement by reducing target installation in the process of building spatial information using 3D laser scanner.

Fusing Algorithm for Dense Point Cloud in Multi-view Stereo (Multi-view Stereo에서 Dense Point Cloud를 위한 Fusing 알고리즘)

  • Han, Hyeon-Deok;Han, Jong-Ki
    • Journal of Broadcast Engineering
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    • v.25 no.5
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    • pp.798-807
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    • 2020
  • As technologies using digital camera have been developed, 3D images can be constructed from the pictures captured by using multiple cameras. The 3D image data is represented in a form of point cloud which consists of 3D coordinate of the data and the related attributes. Various techniques have been proposed to construct the point cloud data. Among them, Structure-from-Motion (SfM) and Multi-view Stereo (MVS) are examples of the image-based technologies in this field. Based on the conventional research, the point cloud data generated from SfM and MVS may be sparse because the depth information may be incorrect and some data have been removed. In this paper, we propose an efficient algorithm to enhance the point cloud so that the density of the generated point cloud increases. Simulation results show that the proposed algorithm outperforms the conventional algorithms objectively and subjectively.

Generating a Rectangular Net from Unorganized Point Cloud Data Using an Implicit Surface Scheme (음 함수 곡면기법을 이용한 임의의 점 군 데이터로부터의 사각망 생성)

  • Yoo, D.J.
    • Korean Journal of Computational Design and Engineering
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    • v.12 no.4
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    • pp.274-282
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    • 2007
  • In this paper, a method of constructing a rectangular net from unorganized point cloud data is presented. In the method an implicit surface that fits the given point data is generated by using principal component analysis(PCA) and adaptive domain decomposition method(ADDM). Then a complete and quality rectangular net can be obtained by extracting voxel data from the implicit surface and projecting exterior faces of extracted voxels onto the implicit surface. The main advantage of the proposed method is that a quality rectangular net can be extracted from randomly scattered 3D points only without any further information. Furthermore the results of this works can be used to obtain many useful information including a slicing data, a solid STL model and a NURBS surface model in many areas involved in treatment of large amount of point data by proper processing of implicit surface and rectangular net generated previously.

Two­Dimensional Warranty Data Modelling (2차원 품질보증데이터 모델링)

  • Jai Wook Baik;Jin Nam Jo
    • Journal of Korean Society for Quality Management
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    • v.31 no.4
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    • pp.219-225
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    • 2003
  • Two­dimensional warranty data can be modelled using two different approaches: two­dimensional point process and one­dimensional point process with usage as a function of age. The first approach has three different models. First of all, bivariate model is appealing but is not appropriate for explaining warranty claims. Next, the rest of the two models (marked point process, and counting and matching on both directions independently) are more appropriate for explaining warranty claims. However, the second one (counting and matching on both directions independently) assumes that the two variables (variables representing the two­dimensions) are independent. Last of all, one­dimensional point process with usage as a function of age is also promising to explain the two­dimensional warranty claims. But the models or variations of them need more investigation to be applicable to real warranty claim data.

Template-Based Reconstruction of Surface Mesh Animation from Point Cloud Animation

  • Park, Sang Il;Lim, Seong-Jae
    • ETRI Journal
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    • v.36 no.6
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    • pp.1008-1015
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    • 2014
  • In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject - the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter-frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame-by-frame basis) while maintaining inter-frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion.

A study on the extended fixed-point arithmetic computation for MPEG audio data processing (MPEG Audio 데이터 처리를 위한 확장된 고정소수점 연산처리에 관한 연구)

  • 한상원;공진흥
    • Proceedings of the IEEK Conference
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    • 2000.06b
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    • pp.250-253
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    • 2000
  • In this paper, we Implement a new arithmetic computation for MPEG audio data to overcome the limitations of real number processing in the fixed-point arithmetics, such as: overheads in processing time and power consumption. We aims at efficiently dealing with real numbers by extending the fixed-point arithmetic manipulation for floating-point numbers in MPEG audio data, and implementing the DSP libraries to support the manipulation and computation of real numbers with the fixed-point resources.

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A Basic Study on Trade-off Analysis of Downsampling for Indoor Point Cloud Data (실내 포인트 클라우드 데이터 Downsampling의 Trade-off 분석을 통한 기초 연구)

  • Kang, Nam-Woo;Oh, Sang-Min;Ryu, Min-Woo;Jung, Yong-Gil;Cho, Hun-hee
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2020.06a
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    • pp.40-41
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    • 2020
  • As the capacity of the 3d scanner developed, the reverse engineering using the 3d scanner is emphasized in the construction industry to obtain the 3d geometric representation of buildings. However, big size of the indoor point cloud data acquired by the 3d scanner restricts the efficient process in the reverse engineering. In order to solve this inefficiency, several pre-processing methods simplifying and denoising the raw point cloud data by the rough standard are developed, but these non-standard methods can cause the inaccurate recognition and removal the key-points. This paper analyzes the correlation between the accuracy of wall recognition and the density of the data, thus proposes the proper method for the raw point cloud data. The result of this study could improve the efficiency of the data processing phase in the reverse engineering for indoor point cloud data.

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Data Transmission Specific Simulation of Transmission Line using HSTL (HSTL을 이용한 전송선로에서의 데이터 전송특성 시뮬레이션)

  • Kim, Soke-Hwan;Hur, Chang-Wu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.8
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    • pp.1777-1781
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    • 2011
  • Tosin backplane system design of this study (Backplane) from the HSTL (High-Speed Transceiver Logic) characteristics of the transmit and receive data using the HSPICE simulations and the actual implementation on the FPGA Data transmission characteristics were described by comparing the simulation results. Simulation and measurement criteria for point to point data transmission characteristics of wire length possible to send and receive data about the speed limits were reviewed. Measured point to point connection to send and receive signals at terminal velocity, the factors that affect the electrical noise around the wire length and showed a very important role.