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Global Scale Integral Volumes

  • Sounak BhattacharyaEmail author
  • Lixin Fan
  • Pouria Babahajiani
  • Moncef Gabbouj
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9913)

Abstract

Integral volume is an important image representation technique, which is useful in many computer vision applications. Processing integral volumes for large scale 3D datasets is challenging due to high memory requirements. The difficulties lie in efficiently computing, storing, querying and updating the integral volume values. In this work, we address the above problems and present a novel solution for processing integral volumes for large scale 3D datasets efficiently. We propose an octree-based method where the worst-case complexity for querying the integral volume of arbitrary regions is \(\mathcal {O}(\log {}n)\), here n is the number of nodes in the octree. We evaluate our proposed method on multi-resolution LiDAR point cloud data. Our work can serve as a tool to fast extract features from large scale 3D datasets, which can be beneficial for computer vision applications.

Keywords

Integral volume Octree Point cloud LiDAR 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Sounak Bhattacharya
    • 1
    Email author
  • Lixin Fan
    • 1
  • Pouria Babahajiani
    • 1
  • Moncef Gabbouj
    • 2
  1. 1.Nokia TechnologiesTampereFinland
  2. 2.Tampere University of TechnologyTampereFinland

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