Clustering as an Approach to 3D Reconstruction Problem

  • Sergey ArkhangelskiyEmail author
  • Ilya Muchnik
Part of the Springer Optimization and Its Applications book series (SOIA, volume 92)


Numerous applications of information technology are connected with 3D-reconstruction task. One of the important special cases is reconstruction using 3D point clouds that are collected by laser range finders and consumer devices like Microsoft Kinect. We present a novel procedure for 3D image registration that is a fundamental step in 3D objects reconstruction. This procedure reduces the task complexity by extracting small subset of potential matches which is enough for accurate registration. We obtain this subset as a result of clustering procedure applied to the broad set of potential matches, where the distance between matches reflects their consistency. Furthermore, we demonstrate the effectiveness of the proposed approach by a set of experiments in comparison with state-of-the-art techniques.


3D object reconstruction Cluster analysis applications Point set registration 


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.MoscowRussia
  2. 2.DIMACS, Rutgers UniversityNew BrunswickUSA

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