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Clustering as an Approach to 3D Reconstruction Problem

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Clusters, Orders, and Trees: Methods and Applications

Part of the book series: Springer Optimization and Its Applications ((SOIA,volume 92))

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Abstract

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.

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Notes

  1. 1.

    https://code.google.com/p/gmmreg.

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Author information

Authors and Affiliations

  1. Moscow, Russia

    Sergey Arkhangelskiy

  2. DIMACS, Rutgers University, New Brunswick, NJ, USA

    Ilya Muchnik

Authors
  1. Sergey Arkhangelskiy
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  2. Ilya Muchnik
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Corresponding author

Correspondence to Sergey Arkhangelskiy .

Editor information

Editors and Affiliations

  1. Department of Higher Mathematics, National Research University Higher School of Economics, Moscow, Russia

    Fuad Aleskerov

  2. Department of Operations, University of Groningen, Groningen, The Netherlands

    Boris Goldengorin

  3. Department of Industrial and Systems Eng, University of Florida, Gainesville, Florida, USA

    Panos M. Pardalos

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Arkhangelskiy, S., Muchnik, I. (2014). Clustering as an Approach to 3D Reconstruction Problem. In: Aleskerov, F., Goldengorin, B., Pardalos, P. (eds) Clusters, Orders, and Trees: Methods and Applications. Springer Optimization and Its Applications, vol 92. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-0742-7_6

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