Investigating Hidden Markov Models capabilities in 2D shape classification

被引：65
|
作者：
Bicego, M [1 ]
Murino, V [1 ]
机构：
[1] Univ Verona, Dipartimento Informat, I-37134 Verona, Italy
来源：
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE | 2004年 / 26卷 / 02期
关键词：
Hidden Markov Models; 2D shape classification; model selection; probabilistic learning;
D O I：
10.1109/TPAMI.2004.1262200
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, Hidden Markov Models (HMMs) are investigated for the purpose of classifying planar shapes represented by their curvature coefficients. In the training phase, special attention is devoted to the initialization and model selection issues, which make the learning phase particularly effective. The results of tests on different data sets show that the proposed system is able to accurately classify objects that were translated, rotated, occluded, or deformed by shearing, also in the presence of noise.
引用
收藏
页码：281 / 286
页数：6
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