• DocumentCode
    27741
  • Title

    Medoid selection from sub-tree leaf nodes for k-medoid clustering-based hierarchical template tree construction

  • Author

    Jung, Ho Gi

  • Author_Institution
    Dept. of Automotive Eng., Hanyang Univ., Seoul, South Korea
  • Volume
    49
  • Issue
    2
  • fYear
    2013
  • fDate
    January 17 2013
  • Firstpage
    108
  • Lastpage
    109
  • Abstract
    A method to construct a hierarchical template tree for pedestrian contour detection by iteratively applying a k-medoid clustering algorithm from the lowest level to the highest level was recently proposed and received much attention. Analysed here is the limitation of the method using lower level medoids as points of the next higher level, and proposed is a method of selecting a medoid from the leaf nodes of sub-trees corresponding to the lower level medoids.
  • Keywords
    edge detection; image matching; iterative methods; pattern clustering; pedestrians; trees (mathematics); unsupervised learning; k-medoid clustering-based hierarchical template tree construction; lower-level medoids; medoid selection; pedestrian contour detection; subtree leaf nodes; template matching;
  • fLanguage
    English
  • Journal_Title
    Electronics Letters
  • Publisher
    iet
  • ISSN
    0013-5194
  • Type

    jour

  • DOI
    10.1049/el.2012.3288
  • Filename
    6420080