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Boundary extraction and simplification of a surface defined by a sparse 3D volume

Published: 23 August 2012 Publication History
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  • Abstract

    Reconstructing surfaces with data coming from an automatic acquisition technique always entails the problem of mass of data. It leads to a mandatory data reduction process. Applying the process to the whole set of points induces an important risk of surface shrinking so that the initial boundary extraction is an important step permitting a simplification inside it. The global surface shape will then be better kept. It is nevertheless required to simplify the boundary, which can be done on the extracted boundary. In this paper, we present a new method to extract and simplify the boundary of an elevation surface given as voxels in a large 3D volume having the characteristics to be sparse since many data are missing. We first present our boundary definition based on mathematical relations between a point and its square neighborhoods. Second, we introduce algorithms to extract such a boundary. Third, we simplify this boundary.

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    Published In

    cover image ACM Other conferences
    SoICT '12: Proceedings of the 3rd Symposium on Information and Communication Technology
    August 2012
    290 pages
    ISBN:9781450312325
    DOI:10.1145/2350716
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 23 August 2012

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    Author Tags

    1. boundary extraction
    2. point clouds
    3. polyline simplification
    4. square neighborhood

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    SoICT '12

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    Overall Acceptance Rate 147 of 318 submissions, 46%

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    • (2022)Research on an Intelligent Identification and Classification Method of Complex Holes in Triangle Meshes for 3D PrintingComputational Intelligence and Neuroscience10.1155/2022/22499252022Online publication date: 1-Jan-2022
    • (2020)Aerial LiDAR Data Augmentation for Direct Point-Cloud VisualisationSensors10.3390/s2007208920:7(2089)Online publication date: 8-Apr-2020
    • (2020)Learning-Based Hole Detection in 3D Point Cloud Towards Hole FillingProcedia Computer Science10.1016/j.procs.2020.04.050171(475-482)Online publication date: 2020
    • (2018)An Improved Method for Restoring the Shape of 3D Point Cloud SurfacesInternational Journal of Synthetic Emotions10.4018/IJSE.20180701039:2(37-53)Online publication date: 1-Jul-2018
    • (2018)An Improved Method for Building A 3D Model from 2D DICOM2018 International Conference on Advanced Computing and Applications (ACOMP)10.1109/ACOMP.2018.00027(125-131)Online publication date: Dec-2018
    • (2018)Filling Hole on the Surface of 3D Point Clouds Based on Reverse Computation of Bezier CurvesInformation Systems Design and Intelligent Applications10.1007/978-981-10-7512-4_34(334-345)Online publication date: 2-Mar-2018
    • (2016)Filling holes on the surface of 3D point clouds based on tangent plane of hole boundary pointsProceedings of the 7th Symposium on Information and Communication Technology10.1145/3011077.3011126(331-338)Online publication date: 8-Dec-2016
    • (2015)Hole Boundary Detection of a Surface of 3D Point Clouds2015 International Conference on Advanced Computing and Applications (ACOMP)10.1109/ACOMP.2015.12(124-129)Online publication date: Dec-2015
    • (2014)Triangulation of an elevation surface structured by a sparse 3D grid2014 IEEE Fifth International Conference on Communications and Electronics (ICCE)10.1109/CCE.2014.6916749(464-469)Online publication date: Jul-2014

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