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
Link To Document