Multilevel streaming for out-of-core surface reconstruction

  • Authors:

  • Matthew Bolitho;Michael Kazhdan;Randal Burns;Hugues Hoppe

  • Affiliations:

  • Johns Hopkins University, Baltimore, MD;Johns Hopkins University, Baltimore, MD;Johns Hopkins University, Baltimore, MD;Microsoft Research, Redmond, WA

  • Venue:
  • SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
  • Year:
  • 2007

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Abstract

Reconstruction of surfaces from huge collections of scanned points often requires out-of-core techniques, and most such techniques involve local computations that are not resilient to data errors. We show that a Poisson-based reconstruction scheme, which considers all points in a global analysis, can be performed efficiently in limited memory using a streaming framework. Specifically, we introduce a multilevel streaming representation, which enables efficient traversal of a sparse octree by concurrently advancing through multiple streams, one per octree level. Remarkably, for our reconstruction application, a sufficiently accurate solution to the global linear system is obtained using a single iteration of cascadic multigrid, which can be evaluated within a single multi-stream pass. We demonstrate scalable performance on several large datasets.