Authors:
Filip Malawski
;
Marek Krupa
and
Ksawery Kapela
Affiliation:
Faculty of Computer Science, AGH University of Science and Technology, Krakow, Poland
Keyword(s):
Action Recognition, Pattern Recognition, Sports Support, Fencing, Assistive Computer Vision.
Abstract:
Typically human action recognition methods focus on the detection and classification of actions. In this work, we consider qualitative evaluation of sports actions, namely in fencing footwork, including technical skill and physical performance. In cooperation with fencing coaches, we designed, recorded, and labeled an extensive dataset including 28 variants of incorrect executions of fencing footwork actions as well as corresponding correct variants. Moreover, the dataset contains action sequences for action recognition tasks. This is the most extensive fencing action dataset collected to date. We propose and evaluate an expert system, based on pose estimation in video data, for measuring relevant motion parameters and distinguishing between correct and incorrect executions of actions. Additionally, we validate a method for temporal segmentation and classification of actions in sequences. The obtained results indicate that the proposed solution can provide relevant feedback in fencin
g training.
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