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Automatic analysis of techniques and body motion patterns in sport

Technology plays an important role in modern sport. Athletes and coaches benefit from the development of methods for automatic analysis of sports motion. Significant progress in this field has been made in recent years, however several relevant challenges still remain. In this work, novel methods for motion analysis are proposed, which address these challenges. A single sports discipline, namely fencing, was chosen for the evaluation of the proposed methods. Fencing is a very technical sport, in which all discussed issues are relevant. The research in this thesis considers three important subjects related to sports analysis. Firstly, recognition of sport-specific actions is addressed. General action recognition methods are not sufficient for sports analysis, since sports actions include different motion pattern and are characterized by different parameters. In particular, actions with similar trajectories, but different dynamics of motion can correspond to different techniques. In this work, novel methods for extraction, selection and fusion of features relevant for sports actions, based on visual and inertial signals, are proposed, and applied to classification of basic fencing footwork actions. The second subject is devoted to the temporal segmentation and qualitative analysis. In order to analyze sports actions it is required to perform temporal segmentation of the continuous motion in the captured training routine. The qualitative analysis of the detected action segments allows to provide the athletes with relevant information regarding the performed actions. In this work novel methods for model-based adaptive signal filtering are proposed, which allow to efficiently detect lunge actions in continuous fencing footwork routine, based on visual and inertial data. The qualitative parameters of the lunge actions are determined, and delivered to fencers in real-time during practice. The third subject is related to the issue of providing feedback.
© Copyright 2019 Julkaistu Tekijä AGH University of Science and Technology Faculty of Computer Science, Electronics and Telecommunications. Kaikki oikeudet pidätetään.

Aiheet: miekkailu liike analyysi biomekaniikka palaute
Aihealueet: biologiset ja lääketieteelliset tieteet
Tagging: Bewegungsmuster
DOI: 10.13140/RG.2.2.25020.28809
Julkaistu: Krakow AGH University of Science and Technology Faculty of Computer Science, Electronics and Telecommunications 2019
Julkaisutyypit: väitöskirja
Kieli: englanti (kieli)
Taso: kehittynyt