The Visual Computer

, Volume 29, Issue 1, pp 69–83 | Cite as

An efficient multi-resolution framework for high quality interactive rendering of massive point clouds using multi-way kd-trees

  • Prashant Goswami
  • Fatih Erol
  • Rahul Mukhi
  • Renato Pajarola
  • Enrico Gobbetti
Original Article


We present an efficient technique for out-of-core multi-resolution construction and high quality interactive visualization of massive point clouds. Our approach introduces a novel hierarchical level of detail (LOD) organization based on multi-way kd-trees, which simplifies memory management and allows control over the LOD-tree height. The LOD tree, constructed bottom up using a fast high-quality point simplification method, is fully balanced and contains all uniformly sized nodes. To this end, we introduce and analyze three efficient point simplification approaches that yield a desired number of high-quality output points. For constant rendering performance, we propose an efficient rendering-on-a-budget method with asynchronous data loading, which delivers fully continuous high quality rendering through LOD geo-morphing and deferred blending. Our algorithm is incorporated in a full end-to-end rendering system, which supports both local rendering and cluster-parallel distributed rendering. The method is evaluated on complex models made of hundreds of millions of point samples.


Point-based rendering Level-of-detail Multi-way kd-tree Entropy-based reduction k-clustering Parallel rendering Geo-morphing 

Supplementary material (74.5 mb)
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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Prashant Goswami
    • 1
  • Fatih Erol
    • 1
  • Rahul Mukhi
    • 3
  • Renato Pajarola
    • 1
  • Enrico Gobbetti
    • 2
  1. 1.Visualization and MultiMedia LabUniversity of ZurichZurichSwitzerland
  2. 2.CRS4Pula (CA)Italy
  3. 3.Department of InformaticsUniversity of ZurichZurichSwitzerland

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