Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)

Enhancing Yoga Pose Estimation Accuracy Using Optimized Mask R-CNN Model

Authors
Deepak Shukla1, *, Maya Rathore1
1Department of Computer Science & Engineering, Oriental University, Indore, India
*Corresponding author. Email: deepakactive@gmail.com
Corresponding Author
Deepak Shukla
Available Online 26 May 2025.
DOI
10.2991/978-94-6463-716-8_30How to use a DOI?
Keywords
Yoga Pose Estimation; Optimized Mask R-CNN; Key point Detection; Feature Aggregation; Human Pose Segmentation; Real-Time Fitness Tracking
Abstract

Yoga pose estimation is important for fitness, healthcare, and rehabilitation applications, existing models such as AlexNet, VGG, and ResNet cannot accurately recognize detailed key points or handle complex postures. To tackle these issues, this paper presents an improved mask R-CNN with better feature aggregation and segmentation and introduces a key point detection branch. Performance analysis demonstrates the effectiveness of our proposed model by improved values of mAP, AP@0. 5, and PCKh@0. 5 metrics. This approach has been experimentally shown to be used for real-time recovery from yoga poses. This work pushes forward the accuracy and scalability of pose estimation for widespread fitness and healthcare applications.

Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
Series
Advances in Intelligent Systems Research
Publication Date
26 May 2025
ISBN
978-94-6463-716-8
ISSN
1951-6851
DOI
10.2991/978-94-6463-716-8_30How to use a DOI?
Copyright
© 2025 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

TY  - CONF
AU  - Deepak Shukla
AU  - Maya Rathore
PY  - 2025
DA  - 2025/05/26
TI  - Enhancing Yoga Pose Estimation Accuracy Using Optimized Mask R-CNN Model
BT  - Proceedings of the International Conference on Recent Advancements and Modernisations in Sustainable Intelligent Technologies and Applications (RAMSITA 2025)
PB  - Atlantis Press
SP  - 373
EP  - 384
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-716-8_30
DO  - 10.2991/978-94-6463-716-8_30
ID  - Shukla2025
ER  -