Welcome to Francis Academic Press

International Journal of Frontiers in Engineering Technology, 2023, 5(5); doi: 10.25236/IJFET.2023.050506.

Shooting Posture Correction System Based on Deep Learning

Author(s)

Yuyang Wu

Corresponding Author:
Yuyang Wu
Affiliation(s)

The United World College of the Atlantic, Wales,UK

Abstract

In view of the lack of effective guidance when people practice shooting posture at home, I designed this model. By importing the video captured by the camera into the model, the model will track the athletes' shoulder, elbow, wrist and other key points in the video, and then calculate the bending Angle of the elbow, and finally judge whether the athletes' shooting posture is standard. The experiment proves that this model has reached the expected goal.

Keywords

Deep learning, Mediapipe

Cite This Paper

Yuyang Wu. Shooting Posture Correction System Based on Deep Learning. International Journal of Frontiers in Engineering Technology (2023), Vol. 5, Issue 5: 35-41. https://doi.org/10.25236/IJFET.2023.050506.

References

[1] Abadi M., et al. "Tensor Flow: Large-Scale Machine Learning on Heterogeneous Distributed Systems." hgpu.org (2015).

[2] Hochreiter S., and J. Schmidhuber. "Long Short-Term Memory." Neural Computation 9.8(1997): 1735-1780.

[3] Lugaresi C., et al. "MediaPipe: A Framework for Building Perception Pipelines." (2019).

[4] Shannon and E. C. . "A Mathematical Theory of Communication." Bell Systems Technical Journal 27.4(1948):623-656.

[5] Fukushima K. "Neocognitron: A self-organizing neural network model for a mechanism of pattern recognition unaffected by shift in position." Biological Cybernetics 36.4(1980): 193-202.