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A study of student movement characteristics in college soccer teaching based on motion capture technology

Juhai Wang

Juhai Wang

Weinan Normal University College of Physical EducationWeinan, China
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Wang, Juhai
  
24 mar 2025
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Publicado en línea: 24 mar 2025
Recibido: 06 nov 2024
Aceptado: 17 feb 2025
DOI: https://doi.org/10.2478/amns-2025-0737
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© 2025 Juhai Wang, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1.

Riemann Pop represents human posture
Riemann Pop represents human posture

Figure 2.

Flow of football action recognition and evaluation system
Flow of football action recognition and evaluation system

Figure 3.

Results of 3D pose reconstruction of the target
Results of 3D pose reconstruction of the target

Figure 4.

3D posture reconstruction results compared with real data
3D posture reconstruction results compared with real data

Figure 5.

Z-axis angular velocity data of football stopping action
Z-axis angular velocity data of football stopping action

Experimental results of football stop recognition

Football experiment 1 2 3 4 5
K-NN 100% 100% 80% 100% 90%
NBC 100% 90% 100% 100% 100%
CART 90% 100% 100% 80% 100%
SVM 100% 100% 100% 100% 100%
DA 80% 70% 50% 40% 50%

Three method attitude difference value comparison results

Graphics Textual method/cm Kalman method/cm Fourier method/cm
1 2.36 6.51 7.43
2 1.89 7.57 8.58
3 2.31 6.29 6.35
4 3.24 7.89 7.82
5 2.27 6.76 8.14
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Calendario de la edición:
1 veces al año
Temas de la revista:
Ciencias de la vida, Ciencias de la vida, otros, Matemáticas, Matemáticas aplicadas, Matemáticas generales, Física, Física, otros
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