• Title/Summary/Keyword: 3차원 포인트 데이터

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Spatial domain-based encapsulation scheme (공간 도메인 기반 캡슐화 방안)

  • Lee, Sangmin;Nam, Kwijung;Rhee, Seongbae;Kim, Kyuheon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2022.06a
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    • pp.818-820
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    • 2022
  • 포인트 클라우드 데이터는 자율 주행 기술, 가상 현실 및 증강 현실에서 사용될 3차원 미디어 중 하나로 각광 받고 있다. 국제 표준화 기구인 MPEG(Moving Picture Expert Group)에서는 포인트 클라우드 데이터의 효율적인 압축을 위해 G-PCC(Geometry-based Point Cloud Compression) 및 V-PCC(Video-based Point Cloud Compression)의 표준화를 진행 중에 있다. 그 중, G-PCC는 본래 단일 프레임의 압축을 수행하는 정지 영상 압축 방식이지만, LiDAR(Light Detection And Ranging) 센서를 통해 획득된 동적 포인트 클라우드 프레임에 대한 압축의 필요성이 대두됨에 따라 G-PCC 그룹에서는 Inter-EM(Exploratory Model)을 신설하여 LiDAR 포인트 클라우드 프레임의 압축에 관한 연구를 시작하였다. Inter-EM의 압축 비트스트림은 G-PCC 비트스트림과 마찬가지로 효과적인 전송 및 소비를 위해 미디어 저장 포맷인 ISOBMFF(ISO-based Media File Format)으로 캡슐화될 수 있다. 이때, 포인트 클라우드 프레임들은 자율 주행 등의 서비스에 사용하기 위해 시간 도메인뿐만 아니라 공간 도메인을 기반으로도 소비될 수 있어야 하지만, 공간 도메인을 기반으로 콘텐츠를 임의 접근하여 소비하는 방식은 기존 2D 영상의 시간 도메인 기반 소비방식과 차이로 인해 기존에 논의된 G-PCC 캡슐화 방안만으로는 지원이 제한된다. 이에, 본 논문에서는 G-PCC 콘텐츠를 공간 도메인에 따라 소비하기 위한 ISOBMFF 캡슐화 방안에 대한 파일 포맷을 제안하고자 한다.

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3D Human Shape Deformation using Deep Learning (딥러닝을 이용한 3차원 사람모델형상 변형)

  • Kim, DaeHee;Hwang, Bon-Woo;Lee, SeungWook;Kwak, Sooyeong
    • Journal of Korea Society of Industrial Information Systems
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    • v.25 no.2
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    • pp.19-27
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    • 2020
  • Recently, rapid and accurate 3D models creation is required in various applications using virtual reality and augmented reality technology. In this paper, we propose an on-site learning based shape deformation method which transforms the clothed 3D human model into the shape of an input point cloud. The proposed algorithm consists of two main parts: one is pre-learning and the other is on-site learning. Each learning consists of encoder, template transformation and decoder network. The proposed network is learned by unsupervised method, which uses the Chamfer distance between the input point cloud form and the template vertices as the loss function. By performing on-site learning on the input point clouds during the inference process, the high accuracy of the inference results can be obtained and presented through experiments.

Matching for Cylinder Shape in Point Cloud Using Random Sample Consensus (Random Sample Consensus를 이용한 포인트 클라우드 실린더 형태 매칭)

  • Jin, YoungHoon
    • Journal of KIISE
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    • v.43 no.5
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    • pp.562-568
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    • 2016
  • Point cloud data can be expressed in a specific coordinate system of a data set with a large number of points, to represent any form that generally has different characteristics in the three-dimensional coordinate space. This paper is aimed at finding a cylindrical pipe in the point cloud of the three-dimensional coordinate system using RANSAC, which is faster than the conventional Hough Transform method. In this study, the proposed cylindrical pipe is estimated by combining the results of parameters based on two mathematical models. The two kinds of mathematical models include a sphere and line, searching the sphere center point and radius in the cylinder, and detecting the cylinder with straightening of center. This method can match cylindrical pipe with relative accuracy; furthermore, the process is rapid except for normal estimation and segmentation. Quick cylinders matching could benefit from laser scanning and reverse engineering construction sectors that require pipe real-time estimates.

ROUTE/DASH-SRD based Point Cloud Content Region Division Transfer and Density Scalability Supporting Method (포인트 클라우드 콘텐츠의 밀도 스케일러빌리티를 지원하는 ROUTE/DASH-SRD 기반 영역 분할 전송 방법)

  • Kim, Doohwan;Park, Seonghwan;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.24 no.5
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    • pp.849-858
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    • 2019
  • Recent developments in computer graphics technology and image processing technology have increased interest in point cloud technology for inputting real space and object information as three-dimensional data. In particular, point cloud technology can accurately provide spatial information, and has attracted a great deal of interest in the field of autonomous vehicles and AR (Augmented Reality)/VR (Virtual Reality). However, in order to provide users with 3D point cloud contents that require more data than conventional 2D images, various technology developments are required. In order to solve these problems, an international standardization organization, MPEG(Moving Picture Experts Group), is in the process of discussing efficient compression and transmission schemes. In this paper, we provide a region division transfer method of 3D point cloud content through extension of existing MPEG-DASH (Dynamic Adaptive Streaming over HTTP)-SRD (Spatial Relationship Description) technology, quality parameters are further defined in the signaling message so that the quality parameters can be selectively determined according to the user's request. We also design a verification platform for ROUTE (Real Time Object Delivery Over Unidirectional Transport)/DASH based heterogeneous network environment and use the results to validate the proposed technology.

A Study On Three-dimensional Face Recognition Model Using PCA : Comparative Studies and Analysis of Model Architectures (PCA를 이용한 3차원 얼굴인식 모델에 관한 연구 : 모델 구조 비교연구 및 해석)

  • Park, Chan-Jun;Oh, Sung-Kwun
    • Proceedings of the KIEE Conference
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    • 2015.07a
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    • pp.1373-1374
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    • 2015
  • 본 논문은 복잡한 비선형 모델링 방법인 다항식 기반 RBF 뉴럴 네트워크(Radial Basis Function Neural Network)와 벡터공간에서 임의의 비선형 경계를 찾아 두 개의 집합을 분류하는 방법으로 주어진 조건하에서 수학적으로 최적의 해를 찾는 SVM(Support Vector Machine)를 사용하여 3차원 얼굴인식 모델을 설계하고 두 모델의 3차원 얼굴 인식률을 비교한다. 3D스캐너를 통해 3차원 얼굴형상을 획득하고 획득한 영상을 전처리 과정에서 포인트 클라우드 정합과 포즈보상을 수행한다. 포즈보상 통해 정면으로 재배치한 영상을 Multiple Point Signature기법을 이용하여 얼굴의 깊이 데이터를 추출한다. 추출된 깊이 데이터를 RBFNN과 SVM의 입력패턴과 출력으로 선정하여 모델을 설계한다. 각 모델의 효율적인 학습을 위해 PCA 알고리즘을 이용하여 고차원의 패턴을 축소하여 모델을 설계하고 인식 성능을 비교 및 확인한다.

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Surgical Simulation Environment for Replacement of Artificial Knee Joint (CT 영상을 이용한 무릎관절 모의 치환 시술 환경)

  • Kim, Dong-Min
    • Journal of IKEEE
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    • v.7 no.1 s.12
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    • pp.119-126
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    • 2003
  • This paper presents a methodology for constructing a surgical simulation environment for the replacement of artificial knee join using CT image data. We provide a user interface of preoperative planning system for performing complex 3-D spatial manipulation and reasoning tasks. Simple manipulation of joystick and mouse has been proved to be both intuitive and accurate for the fitness and the wear expect of joint. The proposed methodology are useful for future virtual medical system where all the components of visualization, automated model generation, and surgical simulation are integrated.

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Reconfiguration of Physical Structure of Vegetation by Voxelization Based on 3D Point Clouds (3차원 포인트 클라우드 기반 복셀화에 의한 식생의 물리적 구조 재구현)

  • Ahn, Myeonghui;Jang, Eun-kyung;Bae, Inhyeok;Ji, Un
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.40 no.6
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    • pp.571-581
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    • 2020
  • Vegetation affects water level change and flow resistance in rivers and impacts waterway ecosystems as a whole. Therefore, it is important to have accurate information about the species, shape, and size of any river vegetation. However, it is not easy to collect full vegetation data on-site, so recent studies have attempted to obtain large amounts of vegetation data using terrestrial laser scanning (TLS). Also, due to the complex shape of vegetation, it is not easy to obtain accurate information about the canopy area, and there are limitations due to a complex range of variables. Therefore, the physical structure of vegetation was analyzed in this study by reconfiguring high-resolution point cloud data collected through 3-dimensional terrestrial laser scanning (3D TLS) in a voxel. Each physical structure was analyzed under three different conditions: a simple vegetation formation without leaves, a complete formation with leaves, and a patch-scale vegetation formation. In the raw data, the outlier and unnecessary data were filtered and removed by Statistical Outlier Removal (SOR), resulting in 17%, 26%, and 25% of data being removed, respectively. Also, vegetation volume by voxel size was reconfigured from post-processed point clouds and compared with vegetation volume; the analysis showed that the margin of error was 8%, 25%, and 63% for each condition, respectively. The larger the size of the target sample, the larger the error. The vegetation surface looked visually similar when resizing the voxel; however, the volume of the entire vegetation was susceptible to error.

The Study on Recording Method for Buried Cultural Property Using Photo Scanning Technique (사진스캐닝 기술에 의한 매장문화재 기록방법에 대한 연구)

  • Koo, Ja-bong
    • Journal of Digital Contents Society
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    • v.16 no.5
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    • pp.835-847
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    • 2015
  • Photo scanning can create point cloud and polygon models like 3D scanners bringing an object into the 3 dimensional world by combining several sheets of photographic information. The created data give us information about planes and sectional forms required for a 2 dimensional survey as well as 3 dimensional figures of buried cultural property. It requires a lot of time to record buried cultural property in the field, however, the photo scanning technique does not need additional equipment and manpower so the work may begin immediately while the property is protected. Moreover, it reduces financial burdens as it creates 3 dimensional data using images acquired by photography but provides the optimal condition to check 3 dimensional information quickly and easily.

Large Point Cloud-based Pipe Shape Reverse Engineering Automation Method (대용량 포인트 클라우드 기반 파이프 형상 역설계 자동화 방법 연구)

  • Kang, Tae-Wook;Kim, Ji-Eum
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.3
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    • pp.692-698
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    • 2016
  • Recently, the facility extension construction and maintenance market portion has increased instead of decreased the newly facility construction. In this context, it is important to examine the reverse engineering of MEP (Mechanical Electrical and Plumbing) facilities, which have the high operation and management cost in the architecture domains. The purpose of this study was to suggest the Large Point Cloud-based Pipe Shape Reverse Engineering Method. To conduct the study, the related researches were surveyed and the reverse engineering automation method of the pipe shapes considering large point cloud was proposed. Based on the method, the prototype was developed and the results were validated. The proposed method is suitable for large data processing considering the validation results because the rendering performance standard deviation related to the 3D point cloud massive data searching was 0.004 seconds.

Probabilistic Map Representation Using Multi-Kinect System (복수의 RGB-D 센서를 사용한 확률기반 3차원 지도작성)

  • Li, Nan Zhe;Hong, Sung Hoon;Lee, Jin Han;Suh, Il Hong
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2015.07a
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    • pp.262-263
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    • 2015
  • 본 논문에서는 마이크로소프트 키넥트 센서를 이용한 실시간 성능의 3차원 환경 복원 알고리즘을 소개한다. 기존의 멀티키넥트 시스템을 확장하여 총 열두대의 키넥트를 사용하는데, 키넥트의 높은 대역폭 문제를 해결하기 위하여 키넥트가 여섯 대씩 연결된 두 대의 데스크탑을 UDP 통신으로 연결하였고, 각 키넥트로부터 들어오는 3차원 포인트클라우드로부터 확률적인 3차원 환경복원을 하기 위하여 옥토맵 알고리즘을 차용하였다. 또한, GPU를 연산에 활용함으로써 실시간 성능을 확보하였다.

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