International Journal of Computer Vision

, Volume 99, Issue 2, pp 215–231

Embedded Voxel Colouring with Adaptive Threshold Selection Using Globally Minimal Surfaces

  • Carlos Leung
  • Ben Appleton
  • Mitchell Buckley
  • Changming Sun

DOI: 10.1007/s11263-012-0525-8

Cite this article as:
Leung, C., Appleton, B., Buckley, M. et al. Int J Comput Vis (2012) 99: 215. doi:10.1007/s11263-012-0525-8


Image-based 3D reconstruction remains a competitive field of research as state-of-the-art algorithms continue to improve. This paper presents a voxel-based algorithm that adapts the earliest space-carving methods and utilises a minimal surface technique to obtain a cleaner result. Embedded Voxel Colouring is built in two stages: (a) progressive voxel carving is used to build a volume of embedded surfaces and (b) the volume is processed to obtain a surface that maximises photo-consistency data in the volume. This algorithm combines the strengths of classical carving techniques with those of minimal surface approaches. We require only a single pass through the voxel volume, this significantly reduces computation time and is the key to the speed of our approach. We also specify three requirements for volumetric reconstruction: monotonic carving order, causality of carving and water-tightness. Experimental results are presented that demonstrate the strengths of this approach.


Volumetric 3D reconstruction Embedded voxel colouring Globally minimal surfaces Monotonic carving order Causality of carving Water-tightness 

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Carlos Leung
    • 1
    • 2
  • Ben Appleton
    • 3
  • Mitchell Buckley
    • 4
    • 5
  • Changming Sun
    • 4
  1. 1.Intelligent Real-Time Imaging and Sensing Group, ITEEThe University of QueenslandBrisbaneAustralia
  2. 2.SuncorpMelbourneAustralia
  3. 3.Google Inc.SydneyAustralia
  4. 4.CSIRO Mathematics, Informatics and StatisticsNorth RydeAustralia
  5. 5.Macquarie UniversitySydneyAustralia

Personalised recommendations