• Title, Summary, Keyword: cloud-point

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Massive 3D Point Cloud Visualization by Generating Artificial Center Points from Multi-Resolution Cube Grid Structure (다단계 정육면체 격자 기반의 가상점 생성을 통한 대용량 3D point cloud 가시화)

  • Yang, Seung-Chan;Han, Soo Hee;Heo, Joon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.30 no.4
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    • pp.335-342
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    • 2012
  • 3D point cloud is widely used in Architecture, Civil Engineering, Medical, Computer Graphics, and many other fields. Due to the improvement of 3D laser scanner, a massive 3D point cloud whose gigantic file size is bigger than computer's memory requires efficient preprocessing and visualization. We suggest a data structure to solve the problem; a 3D point cloud is gradually subdivided by arbitrary-sized cube grids structure and corresponding point cloud subsets generated by the center of each grid cell are achieved while preprocessing. A massive 3D point cloud file is tested through two algorithms: QSplat and ours. Our algorithm, grid-based, showed slower speed in preprocessing but performed faster rendering speed comparing to QSplat. Also our algorithm is further designed to editing or segmentation using the original coordinates of 3D point cloud.

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.

Point cloud removing and rearrangement for reducing bump on 3D mesh (3D Mesh 의 bump 를 감소시키기 위한 Point Cloud 제거 및 재배열 알고리즘)

  • Cha, Sangguk;Han, Jong-Ki
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.266-268
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    • 2020
  • 본 논문에서는 dense point cloud 의 평면영역에서 발생하는 bump 을 줄이기 위한 방법을 제시한다. 이상적인 point cloud 의 평면영역에서 점의 위치의 차이가 균일하다는 특성을 이용하여 점의 위치를 재구성하는 방식을 제시한다. 또한 더 작은 개수의 점으로 물체를 나타낼 수 있으며, 더 작은 잡음이 나타나는 sparse point cloud 의 성질을 고려하여 dense point cloud 의 점의 개수 또한 감소시킨다. 따라서 제안하는 알고리즘을 적용하여 dense point cloud 의 잡음을 감소시키면 평면영역의 bump 감소 및 점 개수의 감소를 통한 데이터 전송 시 더 작은 크기로 보낼 수 있다.

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Three-Dimensional Face Point Cloud Smoothing Based on Modified Anisotropic Diffusion Method

  • Wibowo, Suryo Adhi;Kim, Sungshin
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.2
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    • pp.84-90
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    • 2014
  • This paper presents the results of three-dimensional face point cloud smoothing based on a modified anisotropic diffusion method. The focus of this research was to obtain a 3D face point cloud with a smooth texture and number of vertices equal to the number of vertices input during the smoothing process. Different from other methods, such as using a template D face model, modified anisotropic diffusion only uses basic concepts of convolution and filtering which do not require a complex process. In this research, we used 6D point cloud face data where the first 3D point cloud contained data pertaining to noisy x-, y-, and z-coordinate information, and the other 3D point cloud contained data regarding the red, green, and blue pixel layers as an input system. We used vertex selection to modify the original anisotropic diffusion. The results show that our method has improved performance relative to the original anisotropic diffusion method.

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.

Development of Classification Technique of Point Cloud Data Using Color Information of UAV Image

  • Song, Yong-Hyun;Um, Dae-Yong
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.35 no.4
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    • pp.303-312
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    • 2017
  • This paper indirectly created high density point cloud data using unmanned aerial vehicle image. Then, we tried to suggest new concept of classification technique where particular objects from point cloud data can be selectively classified. For this, we established the classification technique that can be used as search factor in classifying color information in point cloud data. Then, using suggested classification technique, we implemented object classification and analyzed classification accuracy by relative comparison with self-created proof resource. As a result, the possibility of point cloud data classification was observable using the image's information. Furthermore, it was possible to classify particular object's point cloud data in high classification accuracy.

Extraction of Geometric Primitives from Point Cloud Data

  • Kim, Sung-Il;Ahn, Sung-Joon
    • 제어로봇시스템학회:학술대회논문집
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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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Complete 3D Surface Reconstruction from Unstructured Point Cloud

  • Kim, Seok-Il;Li, Rixie
    • Journal of Mechanical Science and Technology
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    • v.20 no.12
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    • pp.2034-2042
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    • 2006
  • In this study, a complete 3D surface reconstruction method is proposed based on the concept that the vertices, of surface model can be completely matched to the unstructured point cloud. In order to generate the initial mesh model from the point cloud, the mesh subdivision of bounding box and shrink-wrapping algorithm are introduced. The control mesh model for well representing the topology of point cloud is derived from the initial mesh model by using the mesh simplification technique based on the original QEM algorithm, and the parametric surface model for approximately representing the geometry of point cloud is derived by applying the local subdivision surface fitting scheme on the control mesh model. And, to reconstruct the complete matching surface model, the insertion of isolated points on the parametric surface model and the mesh optimization are carried out. Especially, the fast 3D surface reconstruction is realized by introducing the voxel-based nearest-point search algorithm, and the simulation results reveal the availability of the proposed surface reconstruction method.

Effect of Additives on the Cloud Point of Polyethylene Glycols

  • Han, Suk-Kyu;Jhun, Byung-Hak
    • Archives of Pharmacal Research
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    • v.7 no.1
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    • pp.1-9
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    • 1984
  • Polyethylene glycol 20, 000 and 6, 000 were found to have an upper consolute temperature, called "cloud point", and the effects of various additives on the polythylene glycols were investigated in this study. Electrolytes lowered the cloud point in proportion to their concentrations through dehydration and electrostriction. It was found that anions played a more important role than cations and the effects of both the cations and the anions clearly followed the classical Hofmeister series. However, the Schultze Hardy rule holds for the effect of anions, and fails for the effect of cations. Salts of large polarizable anions such as iodide and thiocynate rather raised the cloud point, and their effects were ascribed to the fact that they break the water structure and weaken hydrophobic bonding of the polyxyethylene moiety. Nitrates of polyvalent cations also raised the cloud point. This was ascribed to the complex formation between the polyvalent cations and ether oxygens of the polyoxyethylenes. This explained the failure 'of the Schultz-Hardy rule for cations. Uncharged aromatic compounds drastically lowered the clound point, while aliphatic alcohols slightly lowered the cloud point, This result suggests that there might be some interaction between ether oxygens and aromatic nucleus.c nucleus.

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Palette-based Color Attribute Compression for Point Cloud Data

  • Cui, Li;Jang, Euee S.
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.6
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    • pp.3108-3120
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    • 2019
  • Point cloud is widely used in 3D applications due to the recent advancement of 3D data acquisition technology. Polygonal mesh-based compression has been dominant since it can replace many points sharing a surface with a set of vertices with mesh structure. Recent point cloud-based applications demand more point-based interactivity, which makes point cloud compression (PCC) becomes more attractive than 3D mesh compression. Interestingly, an exploration activity has been started to explore the feasibility of PCC standard in MPEG. In this paper, a new color attribute compression method is presented for point cloud data. The proposed method utilizes the spatial redundancy among color attribute data to construct a color palette. The color palette is constructed by using K-means clustering method and each color data in point cloud is represented by the index of its similar color in palette. To further improve the compression efficiency, the spatial redundancy between the indices of neighboring colors is also removed by marking them using a flag bit. Experimental results show that the proposed method achieves a better improvement of RD performance compared with that of the MPEG PCC reference software.