Fine classification of complex motion pattern in fencing

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Abstract

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.

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Mantovani, G., Ravaschio, A., Piaggi Pa, P., & Landi, A. (2010). Fine classification of complex motion pattern in fencing. In Procedia Engineering (Vol. 2, pp. 3423–3428). Elsevier Ltd. https://doi.org/10.1016/j.proeng.2010.04.168

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