REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET

Jayasurya J; Kanimolzhi S; Manoj N; Ramasami S

REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET

March 2023

Vol-9, Issue-2

Paper ID: 19377

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Engineering

Keywords

Tensor flow MoveNet Neural network Yoga pose Classification Computer vision Web application.

Abstract

Presenting a paper about real-time yoga pose classification using tensorflow movenet. The application utilizes a Tensor flow MoveNet to extract key points and a neural network to detect and classify different yoga poses. The Neural network is trained on a large dataset of yoga images, which are pre-processed to extract relevant features using deep learning techniques. The model which is embedded to a website, is designed to work with a webcam or a camera attached to a device and allows users to view themselves in real-time as they perform different yoga poses. The model then provides feedback on the correctness of their pose based on the classification results obtained from the neural network. The proposed web application can be useful for yoga practitioners who want to improve their pose accuracy, as well as for instructors who want to monitor their student’s progress remotely.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Jayasurya J	Bannari Amman Institute of Technology
2	Kanimolzhi S	Bannari Amman Institute of Technology
3	Manoj N	Bannari Amman Institute of Technology
4	Ramasami S	Bannari Amman Institute of Technology

How to Cite

Use the following formats to cite this article in your research.

APA Style

J, Jayasurya, S, Kanimolzhi, N, Manoj, & S, Ramasami (2023). REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET. International Journal of Advance Research and Innovative Ideas In Education, 9(2), 300-306.

MLA Style

J, Jayasurya, et al. "REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, 2023, pp. 300-306.

IEEE Style

Jayasurya J, Kanimolzhi S, Manoj N, and Ramasami S, "REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 2, pp. 300-306, 2023.

Vancouver Style

J Jayasurya, S Kanimolzhi, N Manoj, S Ramasami. REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(2):300-306.

Harvard Style

J, Jayasurya, S, Kanimolzhi, N, Manoj, & S, Ramasami (2023) 'REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET', International Journal of Advance Research and Innovative Ideas In Education, 9(2), pp. 300-306.

Chicago Style

J, Jayasurya, et al. "REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 300-306.

Turabian Style

J, Jayasurya, et al. "REAL TIME DETECTION AND CLASSIFICATION OF YOGA POSE USING TENSORFLOW MOVENET." International Journal of Advance Research and Innovative Ideas In Education 9, no. 2 (2023): 300-306.