Fine Classification of Complex Motion Pattern in Fencing

被引:12
作者
Mantovani, G. [1 ]
Ravaschio, A. [2 ]
Piaggi P, P. [1 ]
Landi, A. [1 ]
机构
[1] Univ Pisa, Fac Engn, Dept Elect Syst & Automat, Largo Lucio Lazzarino 1, I-56122 Pisa, Italy
[2] San Francisco Hosp, Bioengineer Lab, I-55051 Barga Lucca, Italy
来源
ENGINEERING OF SPORT 8: ENGINEERING EMOTION - 8TH CONFERENCE OF THE INTERNATIONAL SPORTS ENGINEERING ASSOCIATION (ISEA) | 2010年 / 2卷 / 02期
关键词
fencing; motion capture; classification; recognition; wavelet analysis; PCA; feature extraction;
D O I
10.1016/j.proeng.2010.04.168
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The subject of this study was fencing and the object was to classify the fundamental motions of fencers by creating a library of movements. Based on this library, thus, the recognition of motions during a real fencing match can be made. Kinematic data were acquired by a motion capture system (Vicon). The automated algorithm that recognized motions is based on three steps: a Principal Component Analysis for data dimension reduction, an innovative wavelet-based analysis of signals and a feature extraction method. The algorithm was tested on high level fencing athletes and it was found to be robust with a 12% of misclassification rate. It gave a description of how atheletes move and showed that in real match athletes do not execute fundamental motions but they mix different techniques in order to surprise the opponent. (C) 2009 Published by Elsevier Ltd.
引用
收藏
页码:3423 / 3428
页数:6
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