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International Conference on Information Computing and Applications

ICICA 2013: Information Computing and Applications pp 398–406Cite as

Research on Fast Loading Large Scale Point Cloud Data File

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 391))

Abstract

To meet the requirement of fast loading large scale point could data file, proposed a new method based on memory pre-allocation and multiple-point concurrency writing technologies which depend on thread pool and memory mapping file mechanism under Windows platform. Test result shows that the new method based on memory pre-allocation and multiple-point concurrency writing technologies improve the performance of loading large-scale point-could data file notably with 220%~300% in loading efficiency, and along with the file size increment, the extra loading time caused by the method is the least compared with the other three methods.

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Author information

Authors and Affiliations

  1. School of Manufacturing Science and Engineering, Southwest University of Science and Technology, 621010, Mianyang, China

    Jiansheng Zhang

  2. Key Lab of Reverse Engineering and Rapid Manufacturing in Sichuan, Southwest University of Science and Technology, 621010, Mianyang, China

    Jiansheng Zhang

Authors
  1. Jiansheng Zhang
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Editor information

Editors and Affiliations

  1. Shanghai Jiao Tong University, 800 Dongchuan Road, Dianxinqunlou 1-401, 200240, Shanghai, China

    Yuhang Yang

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang Avenue, 639798, Singapore, Singapore

    Maode Ma

  3. College of Science, Hebei United University, 063009, Tangshan, Hebei, China

    Baoxiang Liu

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Zhang, J. (2013). Research on Fast Loading Large Scale Point Cloud Data File. In: Yang, Y., Ma, M., Liu, B. (eds) Information Computing and Applications. ICICA 2013. Communications in Computer and Information Science, vol 391. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53932-9_39

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  • DOI: https://doi.org/10.1007/978-3-642-53932-9_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53931-2

  • Online ISBN: 978-3-642-53932-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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