Ensemble techniques have been very successful in pattern recognition. In this work we investigate ensemble solution for shape decomposition. A clustering-based approach is proposed to determine a final decomposition from an ensemble of input decompositions. A recently published performance evaluation framework consisting of a benchmark database with manual ground truth together with evaluation measures is used to demonstrate the benefit of the proposed ensemble technique.


Dissimilarity Measure Ensemble Technique Benchmark Database Majority Vote Rule Majority Vote Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sergej Lewin
    • 1
  • Xiaoyi Jiang
    • 1
  • Achim Clausing
    • 1
  1. 1.Department of Mathematics and Computer ScienceUniversity of MünsterMünsterGermany

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