• DocumentCode
    2478132
  • Title

    Information-theoretic Feature Selection from Unattributed Graphs

  • Author

    Bonev, Boyan ; Escolano, Francisco ; Giorgi, Daniela ; Biasotti, Silvia

  • Author_Institution
    Univ. of Alicante, Alicante, Spain
  • fYear
    2010
  • fDate
    23-26 Aug. 2010
  • Firstpage
    930
  • Lastpage
    933
  • Abstract
    In this work we evaluate purely structural graph measures for 3D objects classification. We extract spectral features from different Reeb graph representations. Information-theoretic feature selection gives an insight on which are the most relevant features.
  • Keywords
    graph theory; information theory; pattern classification; 3D objects classification; different Reeb graph representations; information-theoretic feature selection; structural graph measures; unattributed graphs; Complexity theory; Feature extraction; Kernel; Laplace equations; Measurement; Shape; Three dimensional displays; Classification; Feature extraction; Structural methods for pattern recognition; and analysis; and ranking; reduction; regression;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition (ICPR), 2010 20th International Conference on
  • Conference_Location
    Istanbul
  • ISSN
    1051-4651
  • Print_ISBN
    978-1-4244-7542-1
  • Type

    conf

  • DOI
    10.1109/ICPR.2010.233
  • Filename
    5595827
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2478132