• DocumentCode
    2602074
  • Title

    PCL and ParaView — Connecting the dots

  • Author

    Marion, Pat ; Kwitt, Roland ; Davis, Brad ; Gschwandtner, Michael

  • Author_Institution
    Kitware Inc., Chapel Hill, NC, USA
  • fYear
    2012
  • fDate
    16-21 June 2012
  • Firstpage
    80
  • Lastpage
    85
  • Abstract
    We introduce a novel open-source framework for analyzing and exploring point cloud datasets and algorithms. This is done by integrating the Point Cloud Library (PCL) within ParaView, a parallel scientific visualization tool. In particular, we demonstrate that by wrapping PCL algorithms as VTK1 filters, we can leverage PCL´s functionality in an interactive, easy-to-use manner within ParaView. The proposed approach enables rapid algorithm development in a coherent framework without the need to write custom visualization code. We illustrate the advantages of the framework with usage examples such as segmentation, data annotation and Python integration. Additionally, we build upon ParaView´s inherent parallelization capabilities and present two strong scaling experiments that demonstrate near-linear scaling performance gains in a multi-processor setup.
  • Keywords
    data visualisation; image segmentation; multiprocessing systems; parallel processing; public domain software; PCL algorithms; ParaView; VTK filters; multiprocessor setup; near-linear scaling performance gains; open source framework; parallel scientific visualization tool; point cloud datasets; point cloud library; scaling experiments; Arrays; Cities and towns; Data visualization; Estimation; Image color analysis; Pipelines; Sensors;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Vision and Pattern Recognition Workshops (CVPRW), 2012 IEEE Computer Society Conference on
  • Conference_Location
    Providence, RI
  • ISSN
    2160-7508
  • Print_ISBN
    978-1-4673-1611-8
  • Electronic_ISBN
    2160-7508
  • Type

    conf

  • DOI
    10.1109/CVPRW.2012.6238918
  • Filename
    6238918