DocumentCode :
3775991
Title :
A new shape descriptor based on an angular-linear probability distribution
Author :
Kazunori Iwata;Nobuo Suematsu;Akira Hayashi
Author_Institution :
Graduate School of Information Sciences, Hiroshima City University, Hiroshima 731-3194, Japan
fYear :
2015
Firstpage :
484
Lastpage :
488
Abstract :
Motivated by the increased consideration of probability distributions as local descriptors of shape, we propose a local descriptor based on a bivariate circular distribution. Although some bivariate circular distributions are difficult to compute, our descriptor is computationally feasible because it is a generalization of the mixture of von Mises distributions. Using various shapes formed by line drawings, we show that our descriptor is more effective in shape retrieval than several conventional local descriptors.
Keywords :
"Shape","Probability density function","Probability distribution","Cost function","Pattern recognition","Context","Density functional theory"
Publisher :
ieee
Conference_Titel :
Pattern Recognition (ACPR), 2015 3rd IAPR Asian Conference on
Electronic_ISBN :
2327-0985
Type :
conf
DOI :
10.1109/ACPR.2015.7486550
Filename :
7486550
Link To Document :
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