Hierarchical Clustering of Sensorimotor Features

  • Konrad Gadzicki
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5803)


In this paper a method for clustering patterns represented by sets of sensorimotor features is introduced. Sensorimotor features as a biologically inspired representation have proofed to be working for the recognition task, but a method for unsupervised learning of classes from a set of patterns has been missing yet. By utilization of Self-Organizing Maps as a intermediate step, a hierarchy can be build with standard agglomerative clustering methods.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Konrad Gadzicki
    • 1
  1. 1.University of BremenBremenGermany

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