Title: Automatic recognition of javelin athletes' throwing angle based on recognisable statistical characteristics

Authors: Zhe Dong; Xiongying Wang

Addresses: College of Physical Education, Hu Nan City University, Yi yang 413000, China ' College of Physical Education, Hu Nan City University, Yi yang 413000, China

Abstract: In order to overcome the problem that the traditional recognition method has poor statistical performance on the regularity of body feature data before recognising the throwing angle, which leads to the deviation of javelin flight trajectory judgment results, this paper proposes an automatic recognition method of javelin athletes' throwing angle based on the recognisable statistical characteristics. Firstly, the technical characteristics of javelin throwers of different genders are extracted by using the statistical process of distinguishing features. Then, the angle of recognition equipment is calibrated and the position of trigger signal is combined to realise the automatic recognition of javelin throw angle. Experimental results show that: the javelin flight trajectory identified by this method is the closest to the actual trajectory; the recognition accuracy of the throwing angle can reach more than 98%. It shows that the method can effectively realise the accurate recognition of javelin athletes' throwing angle.

Keywords: recognisable statistical characteristics; javelin movement; throwing angle recognition; two-dimensional image; trigger signal position; recognition accuracy.

DOI: 10.1504/IJBM.2022.124678

International Journal of Biometrics, 2022 Vol.14 No.3/4, pp.408 - 420

Received: 25 Sep 2020
Accepted: 15 Dec 2020

Published online: 05 Aug 2022 *

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