Design and Implementation of Lightweight Fitness System Based on Mediapipe Framework

Jialei Shi, Ruohan Lin, Bohao Zhou
Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing, PMLR 278:240-250, 2025.

Abstract

With the development of the social economy, people are paying increasing attention to personal health and regard fitness as an essential way to improve physical quality. However, China has a large population and cannot provide high-quality physical education for everyone, facing enormous logistical and resource challenges. Therefore, this study designed a lightweight, intelligent fitness system based on Mediapipe and OpenCV, which offers high adaptability, portability, and a lightweight design, particularly for micro mobile devices. The system can provide users with more convenient, personalized, and efficient training methods. This paper offers an in-depth introduction to the functional framework and development details of the system and conducts functional testing and comparison. According to the experimental results, the system shows good performance, stable operation, and high recognition rate, achieving the expected experimental goal.

Cite this Paper

BibTeX
@InProceedings{pmlr-v278-shi25a, title = {Design and Implementation of Lightweight Fitness System Based on Mediapipe Framework}, author = {Shi, Jialei and Lin, Ruohan and Zhou, Bohao}, booktitle = {Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing}, pages = {240--250}, year = {2025}, editor = {Zeng, Nianyin and Pachori, Ram Bilas and Wang, Dongshu}, volume = {278}, series = {Proceedings of Machine Learning Research}, month = {25--27 Apr}, publisher = {PMLR}, pdf = {https://raw.githubusercontent.com/mlresearch/v278/main/assets/shi25a/shi25a.pdf}, url = {https://proceedings.mlr.press/v278/shi25a.html}, abstract = {With the development of the social economy, people are paying increasing attention to personal health and regard fitness as an essential way to improve physical quality. However, China has a large population and cannot provide high-quality physical education for everyone, facing enormous logistical and resource challenges. Therefore, this study designed a lightweight, intelligent fitness system based on Mediapipe and OpenCV, which offers high adaptability, portability, and a lightweight design, particularly for micro mobile devices. The system can provide users with more convenient, personalized, and efficient training methods. This paper offers an in-depth introduction to the functional framework and development details of the system and conducts functional testing and comparison. According to the experimental results, the system shows good performance, stable operation, and high recognition rate, achieving the expected experimental goal.} }
Endnote
%0 Conference Paper %T Design and Implementation of Lightweight Fitness System Based on Mediapipe Framework %A Jialei Shi %A Ruohan Lin %A Bohao Zhou %B Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing %C Proceedings of Machine Learning Research %D 2025 %E Nianyin Zeng %E Ram Bilas Pachori %E Dongshu Wang %F pmlr-v278-shi25a %I PMLR %P 240--250 %U https://proceedings.mlr.press/v278/shi25a.html %V 278 %X With the development of the social economy, people are paying increasing attention to personal health and regard fitness as an essential way to improve physical quality. However, China has a large population and cannot provide high-quality physical education for everyone, facing enormous logistical and resource challenges. Therefore, this study designed a lightweight, intelligent fitness system based on Mediapipe and OpenCV, which offers high adaptability, portability, and a lightweight design, particularly for micro mobile devices. The system can provide users with more convenient, personalized, and efficient training methods. This paper offers an in-depth introduction to the functional framework and development details of the system and conducts functional testing and comparison. According to the experimental results, the system shows good performance, stable operation, and high recognition rate, achieving the expected experimental goal.
APA
Shi, J., Lin, R. & Zhou, B.. (2025). Design and Implementation of Lightweight Fitness System Based on Mediapipe Framework. Proceedings of 2025 2nd International Conference on Machine Learning and Intelligent Computing, in Proceedings of Machine Learning Research 278:240-250 Available from https://proceedings.mlr.press/v278/shi25a.html.

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