• Title/Summary/Keyword: point-cloud

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Improvement of point cloud data using 2D super resolution network (2D super resolution network를 이용한 Point Cloud 데이터 개선)

  • Park, Seong-Hwan;Kim, Kyu-Heon
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2021.06a
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    • pp.16-18
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    • 2021
  • 미디어 기술은 사용자가 더욱 몰입감을 느낄 수 있는 방향으로 개발되어 왔다. 이러한 흐름에 따라 기존의 2D 이미지에 비해 깊이감을 느낄 수 있는 증강 현실, 가상 현실 등 3D 공간 데이터를 활용하는 미디어가 주목을 받고 있다. 포인트 클라우드는 수많은 3차원 좌표를 가진 여러 개의 점들로 구성된 데이터 형식이므로 각각의 점들에 대한 좌표 및 색상 정보를 사용하여 3D 미디어를 표현한다. 고정된 크기의 해상도를 갖는 2D 이미지와 다르게 포인트 클라우드는 포인트의 개수에 따라 용량이 유동적이며, 이를 기존의 비디오 코덱을 사용하여 압축하기 위해 국제 표준기구인 MPEG(Moving Picture Experts Group)에서는 Video-based Point Cloud Compression (V-PCC)을 제정하였다. V-PCC는 3D 포인트 클라우드 데이터를 직교 평면 벡터를 이용하여 2D 패치로 분해하고 이러한 패치를 2D 이미지에 배치한 다음 기존의 2D 비디오 코덱을 사용하여 압축한다. 본 논문에서는 앞서 설명한 2D 패치 이미지에 super resolution network를 적용함으로써 3D 포인트 클라우드의 성능 향상하는 방안을 제안한다.

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Development of LiDAR Drone-based Point Cloud Data Accuracy Verification Technology (드론 LiDAR를 활용한 점군 데이터 정확도 검증 기술 개발)

  • Jae-Woo Park;Dong-Jun Yeom
    • Journal of the Korean Society of Industry Convergence
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    • v.26 no.6_3
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    • pp.1233-1241
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    • 2023
  • This paper investigates the efficient application of drone LiDAR technology for acquiring precise point cloud data in construction and civil engineering. A structured workflow encompassing data acquisition, processing, and accuracy verification is introduced. Practical testing on a construction site affirms that drone LiDAR surveying yields accurate and reliable data across various applications. With a focus on accuracy and verification, the results contribute to the progression of surveying methodologies in construction and civil engineering. The findings provide valuable insights into the dynamic technological landscape of these fields, establishing a foundation for more effective and precise surveying techniques. This study underscores the transformative potential of drone LiDAR technology in shaping the future of construction and civil engineering survey practices.

A New Locomotor Evaluation System for Mouses Based on Continuous Shooting Images (연속 촬영 이미지를 이용한 Mouse의 운동 능력 평가 시스템)

  • Kwak, Ho-Young;Huh, Jisoon;Lee, Won Joo
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.1
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    • pp.153-161
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    • 2015
  • In this paper, we propose a locomotor evaluation System for mouse based on continuous shooting images. In the field of veterinary medicine and animal studies are subjected to using the mouse for the quality of human life. In particular, during the experiments using the artificially created mice injury, through a variety of scoring and a lot of experiments to measure the extent of recovery from the injury. The traditional method of measuring the quantity of exercise while in this experiment was made of a method for directly observing person. The proposed system performs the continuous shooting per unit of time specified by the movement of the mouse is extracted from a continuous image shooting with the outline of a mouse point cloud. And using the extracted point cloud to extract again the inner contour of the body of the mouse. So using the new point cloud obtained its center, Then, using the center point calculated by accumulating the distance between two points on locomotor evaluation system design and implement to obtain the total distance the mouse moves over a unit of time.

Point Cloud Video Codec using 3D DCT based Motion Estimation and Motion Compensation (3D DCT를 활용한 포인트 클라우드의 움직임 예측 및 보상 기법)

  • Lee, Minseok;Kim, Boyeun;Yoon, Sangeun;Hwang, Yonghae;Kim, Junsik;Kim, Kyuheon
    • Journal of Broadcast Engineering
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    • v.26 no.6
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    • pp.680-691
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    • 2021
  • Due to the recent developments of attaining 3D contents by using devices such as 3D scanners, the diversity of the contents being used in AR(Augmented Reality)/VR(Virutal Reality) fields is significantly increasing. There are several ways to represent 3D data, and using point clouds is one of them. A point cloud is a cluster of points, having the advantage of being able to attain actual 3D data with high precision. However, in order to express 3D contents, much more data is required compared to that of 2D images. The size of data needed to represent dynamic 3D point cloud objects that consists of multiple frames is especially big, and that is why an efficient compression technology for this kind of data must be developed. In this paper, a motion estimation and compensation method for dynamic point cloud objects using 3D DCT is proposed. This will lead to switching the 3D video frames into I frames and P frames, which ensures higher compression ratio. Then, we confirm the compression efficiency of the proposed technology by comparing it with the anchor technology, an Intra-frame based compression method, and 2D-DCT based V-PCC.

Underground Facility Survey and 3D Visualization Using Drones (드론을 활용한 지하시설물측량 및 3D 시각화)

  • Kim, Min Su;An, Hyo Won;Choi, Jae Hoon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.1
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    • pp.1-14
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    • 2022
  • In order to conduct rapid, accurate and safe surveying at the excavation site, In this study, the possibility of underground facility survey using drones and the expected effect of 3D visualization were obtained as follows. Phantom4Pro 20MP drones have a 30m flight altitude and a redundant 85% flight plan, securing a GSD (Ground Sampling Distance) value of 0.85mm and 4points of GCP (Groud Control Point)and 2points of check point were calculated, and 7.3mm of ground control point and 11mm of check point were obtained. The importance of GCP was confirmed when measured with low-cost drones. If there is no ground reference point, the error range of X value is derived from -81.2 cm to +90.0 cm, and the error range of Y value is +6.8 cm to 155.9 cm. This study classifies point cloud data using the Pix4D program. I'm sorting underground facility data and road pavement data, and visualized 3D data of road and underground facilities of actual model through overlapping process. Overlaid point cloud data can be used to check the location and depth of the place you want through the Open Source program CloudCompare. This study will become a new paradigm of underground facility surveying.

3D Mesh Creation using 2D Delaunay Triangulation of 3D Point Clouds (2차원 딜로니 삼각화를 이용한 3차원 메시 생성)

  • Choi, Ji-Hoon;Yoon, Jong-Hyun;Park, Jong-Seung
    • Journal of the Korea Computer Graphics Society
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    • v.13 no.4
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    • pp.21-27
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    • 2007
  • The 3D Delaunay triangulation is the most widely used method for the mesh creation via the triangulation of a 3D point cloud. However, the method involves a heavy computational cost and, hence, in many interactive applications, it is not appropriate for surface triangulation. In this paper, we propose an efficient triangulation method to create a surface mesh from a 3D point cloud. We divide a set of object points into multiple subsets and apply the 2D Delaunay triangulation to each subset. A given 3D point cloud is cut into slices with respect to the OBB(Oriented Bounding Box) of the point set. The 2D Delaunay triangulation is applied to each subset producing a partial triangulation. The sum of the partial triangulations constitutes the global mesh. As a postprocessing process, we eliminate false edges introduced in the split steps of the triangulation and improve the results. The proposed method can be effectively applied to various image-based modeling applications.

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Designing a Reinforcement Learning-Based 3D Object Reconstruction Data Acquisition Simulation (강화학습 기반 3D 객체복원 데이터 획득 시뮬레이션 설계)

  • Young-Hoon Jin
    • Journal of Internet of Things and Convergence
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    • v.9 no.6
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    • pp.11-16
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    • 2023
  • The technology of 3D reconstruction, primarily relying on point cloud data, is essential for digitizing objects or spaces. This paper aims to utilize reinforcement learning to achieve the acquisition of point clouds in a given environment. To accomplish this, a simulation environment is constructed using Unity, and reinforcement learning is implemented using the Unity package known as ML-Agents. The process of point cloud acquisition involves initially setting a goal and calculating a traversable path around the goal. The traversal path is segmented at regular intervals, with rewards assigned at each step. To prevent the agent from deviating from the path, rewards are increased. Additionally, rewards are granted each time the agent fixates on the goal during traversal, facilitating the learning of optimal points for point cloud acquisition at each traversal step. Experimental results demonstrate that despite the variability in traversal paths, the approach enables the acquisition of relatively accurate point clouds.

The Security Architecture for Secure Cloud Computing Environment

  • Choi, Sang-Yong;Jeong, Kimoon
    • Journal of the Korea Society of Computer and Information
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    • v.23 no.12
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    • pp.81-87
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    • 2018
  • Cloud computing is a computing environment in which users borrow as many IT resources as they need to, and use them over the network at any point in time. This is the concept of leasing and using as many IT resources as needed to lower IT resource usage costs and increase efficiency. Recently, cloud computing is emerging to provide stable service and volume of data along with major technological developments such as the Internet of Things, artificial intelligence and big data. However, for a more secure cloud environment, the importance of perimeter security such as shared resources and resulting secure data storage and access control is growing. This paper analyzes security threats in cloud computing environments and proposes a security architecture for effective response.

Technology Standard Trends in Distributed and Edge Cloud Computing (분산 및 에지 클라우드 기술 표준 동향)

  • M.K. In;K.C. Lee;S.Y. Lee
    • Electronics and Telecommunications Trends
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    • v.39 no.3
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    • pp.69-78
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    • 2024
  • Cloud computing technology based on centralized high-performance computing has brought about major changes across the information technology industry and led to new paradigms. However, with the rapid development of the industry and increasing need for mass generation and real-time processing of data across various fields, centralized cloud computing is lagging behind the demand. This is particularly critical in emerging technologies such as autonomous driving, the metaverse, and augmented/virtual reality that require the provision of services with ultralow latency for real-time performance. To address existing limitations, distributed and edge cloud computing technologies have recently gained attention. These technologies allow for data to be processed and analyzed closer to their point of generation, substantially reducing the response times and optimizing the network bandwidth usage. We describe distributed and edge cloud computing technologies and explore the latest trends in their standardization.

Pipe Surface Reconstruction Using Shrinking (수축을 이용한 파이프 곡면의 복원)

  • Lee, In-Kwon
    • Journal of the Korea Computer Graphics Society
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    • v.5 no.2
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    • pp.1-7
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    • 1999
  • We present an algorithm to reconstruct a pipe surface from a set of unorganized points. A pipe surface is defined by a spine curve and a radius of a swept sphere. In this paper, by using the shrinking and moving least-squares methods, a point cloud is reduced to a thin curve-like point set that can be easily approximated with a spine curve of a pipe surface. The distance between a point in the thin point cloud and a corresponding point in the original point set represents the radius of a swept sphere of a pipe surface.

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