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The effect of real-time pose recognition on badminton learning performance

Kuo-Chin Lin, Cheng‐Wen Ko, Hui-Chun Hung, Nian‐Shing Chen

2021Interactive Learning Environments27 citationsDOI

Abstract

Badminton is a very popular subject in Physical Education (PE). Many students enroll badminton courses in every semester which pose a tremendous teaching load to the instructors. The one-on-one guiding/feedback time provided by the instructor to each student is also greatly reduced. To overcome this challenge, some studies have tried to adopt pose recognition technique in teaching badminton. However, the lack of mobility and recognition accuracy problems hinder its applicability. To address this issue, a new pose recognition technique, OpenPose, was employed to develop a real-time pose recognition badminton teaching APP in this study. The APP was then installed on a mobile device to enhance badminton smash skill learning performance. The scores distribution of the experimental group shows majority of students achieved satisfactory performance, this implies the badminton teaching APP is helpful to all students no matter what their initial skill levels are.

Topics & Concepts

Computer scienceMobile appsMultimediaMobile deviceHuman–computer interactionMathematics educationPsychologyWorld Wide WebVideo Analysis and SummarizationHuman Pose and Action RecognitionSports and Physical Education Research
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