• Title/Summary/Keyword: 3D PointCloud

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Calculation of Key Blocks' Safety Ratio based on Discontinuity Analysis (불연속면 분석에 근거한 쐐기블록 안전율 계산)

  • Kim, Eunsung;Noh, Sanghun;Lee, Sang-Soon
    • Journal of the Korean Geotechnical Society
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    • v.40 no.3
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    • pp.101-108
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    • 2024
  • A system with the ability to recognize potential key blocks during tunnel construction by analyzing the rock face was developed in this study. This system predicts the formation of key blocks in advance and evaluates their safety factors. A laser scanner was used to collect a three-dimensional point cloud of the rock face, which was then utilized to model the excavation surface and derive the joint surfaces. Because joint surfaces have specific strikes and dip angles, the key blocks formed by these surfaces are deduced through iterative calculations, and the safety factor of each key block can be calculated accordingly. The model experiments confirmed the accuracy of the system's output in terms of the joint surface characteristics. By inputting the joint surface information, the calculated safety factors were compared with those from the existing commercial software, demonstrating stable calculation results within a 1% error margin.

A Study on the Changes in the Physical Environment of Resources in Rural Areas Using UAV -Focusing on Resources in Galsan-Myeon, Hongseong-gun- (무인항공기를 활용한 농촌 지역자원의 물리적 환경변화 분석연구 - 홍성군 갈산면 지역자원을 중심으로 -)

  • An, Phil-Gyun;Kim, Sang-Bum;Cho, Suk-Yeong;Eom, Seong-Jun;Kim, Young-Gyun;Cho, Han-Sol
    • Journal of the Korean Institute of Rural Architecture
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    • v.23 no.4
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    • pp.1-12
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    • 2021
  • Recently, the use of unmanned aerial vehicles (UAVs) is increasing in the field of land information acquisition and terrain exploration through high-altitude aerial photography. High-altitude aerial photography is suitable for large-scale geographic information collection, but has the disadvantage that it is difficult to accurately collect small-scale geographic information. Therefore, this study used low-altitude UAV to monitor changes in small rural spaces around rural resources, and the results are as follows. First, the low-altitude aerial imagery had a very high spatial resolution, so it was effective in reading and analyzing topographic features. Second, an area with a large number of aerial images and a complex topography had a large amount of point clouds to be extracted, and the number of point clouds affects the three-dimensional quality of rural space. Third, 3D mapping technology using point cloud is effective for monitoring rural space and rural resources because it enables observation and comparison of parts that cannot be read from general aerial images. In this study, the possibility of rural space analysis of low-altitude UAV was verified through aerial photography and analysis, and the effect of 3D mapping on rural space monitoring was visually analyzed. If data acquired by low-altitude UAV are used in various forms such as GIS analysis and topographic map production it is expected to be used as basic data for rural planning to maintain and preserve the rural environment.

Explanable Artificial Intelligence Study based on Blockchain Using Point Cloud (포인트 클라우드를 이용한 블록체인 기반 설명 가능한 인공지능 연구)

  • Hong, Sunghyuck
    • Journal of Convergence for Information Technology
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    • v.11 no.8
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    • pp.36-41
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    • 2021
  • Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

The 3D Modeling Data Production Method Using Drones Photographic Scanning Technology (드론 촬영 기반 사진 스캐닝 기술을 활용한 3D 모델링데이터 생성방법에 관한 연구)

  • Lee, Junsang;Lee, Imgeun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.22 no.6
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    • pp.874-880
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    • 2018
  • 3D modeling is extensively used in the field of architecture, machinery and contents production such as movies. Modeling is a time-consuming task. In order to compensate for these drawbacks, attempts have recently been made to reduce the production period by applying 3D scanning technology. 3D scanning for small objects can be done directly with laser or optics, but large buildings and sculptures require expensive equipment, which makes it difficult to acquire data directly. In this study, 3D modeling data for a large object is acquired using photometry with using drones to acquire the image data. The maintenance method for uniform spacing between the sculpture and the drone, the measurement method for the flight line were presented. In addition, we presented a production environment that can utilize the obtained 3D point cloud data for animation and a rendered animation result to find ways to make it in various environments.

Geometry Reconstruction Using Dictionary Learning of 3D Shape Features (3차원 형태 특징의 사전 학습을 이용한 기하 복원)

  • Hwang, Jung-Min;Yoon, Yeo-Jin;Choi, Soo-Mi
    • Journal of the Korea Computer Graphics Society
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    • v.23 no.1
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    • pp.57-65
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    • 2017
  • In this paper, we present a dictionary learning method for reducing errors in point cloud models and reconstructing their geometry. For this, 3D feature information is extracted from the models which have a similar shape characteristic as the target model. Then a dictionary is constructed and the geometry is reconstructed using the dictionary. The presented method in this paper consists of the following three steps. First, a geometric patch is constructed from a similar model. Second, a morphological 3D feature of the acquired patch is learned. Third, a geometry reconstruction is performed using the learned dictionary. Finally, the error between the original model and the reconstruction result is calculated, and the accuracy of the reconstruction result is checked.

Common Optical System for the Fusion of Three-dimensional Images and Infrared Images

  • Kim, Duck-Lae;Jung, Bo Hee;Kong, Hyun-Bae;Ok, Chang-Min;Lee, Seung-Tae
    • Current Optics and Photonics
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    • v.3 no.1
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    • pp.8-15
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    • 2019
  • We describe a common optical system that merges a LADAR system, which generates a point cloud, and a more traditional imaging system operating in the LWIR, which generates image data. The optimum diameter of the entrance pupil was determined by analysis of detection ranges of the LADAR sensor, and the result was applied to design a common optical system using LADAR sensors and LWIR sensors; the performance of these sensors was then evaluated. The minimum detectable signal of the $128{\times}128-pixel$ LADAR detector was calculated as 20.5 nW. The detection range of the LADAR optical system was calculated to be 1,000 m, and according to the results, the optimum diameter of the entrance pupil was determined to be 15.7 cm. The modulation transfer function (MTF) in relation to the diffraction limit of the designed common optical system was analyzed and, according to the results, the MTF of the LADAR optical system was 98.8% at the spatial frequency of 5 cycles per millimeter, while that of the LWIR optical system was 92.4% at the spatial frequency of 29 cycles per millimeter. The detection, recognition, and identification distances of the LWIR optical system were determined to be 5.12, 2.82, and 1.96 km, respectively.

Stereoscopic Video Compositing with a DSLR and Depth Information by Kinect (키넥트 깊이 정보와 DSLR을 이용한 스테레오스코픽 비디오 합성)

  • Kwon, Soon-Chul;Kang, Won-Young;Jeong, Yeong-Hu;Lee, Seung-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.38C no.10
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    • pp.920-927
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    • 2013
  • Chroma key technique which composes images by separating an object from its background in specific color has restrictions on color and space. Especially, unlike general chroma key technique, image composition for stereo 3D display requires natural image composition method in 3D space. The thesis attempted to compose images in 3D space using depth keying method which uses high resolution depth information. High resolution depth map was obtained through camera calibration between the DSLR and Kinect sensor. 3D mesh model was created by the high resolution depth information and mapped with RGB color value. Object was converted into point cloud type in 3D space after separating it from its background according to depth information. The image in which 3D virtual background and object are composed obtained and played stereo 3D images using a virtual camera.

Performance Analysis of 3DoF+ Video Coding Using V3C (V3C 기반 3DoF+ 비디오 부호화 성능 분석)

  • Lee, Ye-Jin;Yoon, Yong-Uk;Kim, Jae-Gon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2020.11a
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    • pp.166-168
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    • 2020
  • MPEG 비디오 그룹은 MPEG-I 표준의 일부로 포인트 클라우드(Point Cloud) 압축을 위한 비디오 기반 포인트 클라우드 부호화(V-PCC)와 몰입형(immersive) 비디오 압축을 위한 MPEG Immersive Video(MIV) 표준을 개발하고 있다. 최근에는 포인트 클라우드 및 몰입형 비디오와 같은 체적형(volumetric) 비디오를 모두 압축할 수 있도록 V-PCC 와 MIV 를 통합한 V3C(Visual Volumetric Video-based Coding) 표준화를 진행하고 있다. 본 논문에서는 V3C 코덱을 사용한 3DoF+(3 Degree of Freedom plus) 비디오 부호화 방안을 분석한다. 또한 V3C 코덱의 2D 코덱으로 기존 HEVC 대신 VVC 를 사용할 경우의 부호화 성능 향상을 분석한다.

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Application of 3D Chain Code for Object Recognition and Analysis (객체인식과 분석을 위한 3D 체인코드의 적용)

  • Park, So-Young;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.5
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    • pp.459-469
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    • 2011
  • There are various factors for determining object shape, such as size, slope and its direction, curvature, length, surface, angles between lines or planes, distribution of the model key points, and so on. Most of the object description and recognition methods are for the 2D space not for the 3D object space where the objects actually exist. In this study, 3D chain code operator, which is basically extension of 2D chain code, was proposed for object description and analysis in 3D space. Results show that the sequence of the 3D chain codes could be basis of a top-down approach for object recognition and modeling. In addition, the proposed method could be applicable to segment point cloud data such as LiDAR data.

Fusion of point cloud and integral-imaging technique for full-parallax 3D display (완전시차를 가지는 3 차원 디스플레이를 위한 포인트 클라우드와 집적영상기술의 융합)

  • Hong, Seokmin;Kang, Hyunmin;Oh, Hyunju;Park, Jiyong
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.292-294
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    • 2022
  • 본 논문은 3 차원 이미징 기술과 컴퓨터 그래픽스 기반의 시뮬레이션 분야에서 매우 성공적인 두 기술의 융합을 기반으로 진행한 연구를 제안한다. 먼저 3 차원 디스플레이 시스템에 재생할 집적 영상 이미지를 생성하는 방법에 대해 설명한다. 이는 3 차원 포인트 클라우드에서 가상 핀홀 배열로 입사각을 역투영하는 계산방식을 통해 해당 이미지를 생성한다. 우리는 재생되는 3 차원 영상의 초점면을 자유롭게 선택하는 방법에 대해서도 설명한다. 또한, 복수의 관찰자에게 동시에 다양한 시점 정보를 기반으로 몰입감 넘치는 3 차원 영상을 제공하는 3 차원 디스플레이 시스템을 소개하고, 다양한 실험결과를 기반으로 결론을 제시한다.