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Volume 29 Issue 1
Jan.  2016
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Journal of Southwest Jiaotong University  > 2016  >  29(1): 78-84.
ZHANG Junfeng, XU Dehe, WANG Xiaodong. Management Algorithm of Point-Cloud Data Based on Octree Concerned with Adaptive Levels of Detail[J]. Journal of Southwest Jiaotong University, 2016, 29(1): 78-84. doi: 10.3969/j.issn.0258-2724.2016.01.012
Citation: ZHANG Junfeng, XU Dehe, WANG Xiaodong. Management Algorithm of Point-Cloud Data Based on Octree Concerned with Adaptive Levels of Detail[J]. Journal of Southwest Jiaotong University, 2016, 29(1): 78-84. doi: 10.3969/j.issn.0258-2724.2016.01.012
shu

Management Algorithm of Point-Cloud Data Based on Octree Concerned with Adaptive Levels of Detail

doi: 10.3969/j.issn.0258-2724.2016.01.012
  • Received Date: 19 Aug 2014
  • Publish Date: 25 Jan 2016
    Abstract
  • Large-scale point-cloud data are not easy to organize effectively and have great redundancy at dynamic visualization, and it is hard to realize the adaptive display. Aiming at these problems, a new algorithm concerned with the levels of detail (LOD) of point-cloud expression on the basis of octree structure was proposed. The algorithm assigned every scanning point into an octree node, and integrated top-down division with down-top calculation as the pretreatment strategy to reduce the amount of real-time calculation. Then it made any region meet the accuracy requirement and display speed automatically by building conservative simulation-error evaluation criteria. Furthermore, with the help of acceleration methods, large-scale point-cloud data could be organized effectively and expressed smoothly with little data redundancy. Preliminary experiments show that the algorithm has abilities to overcome the shortcoming of the classical R-tree methods; meanwhile, with the support of optimized pretreatment and assistant acceleration methods, the amount of real-time calculation is small and the time of each frame can hold within 0.04 s easily.

     

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