Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Intelligent Sports Video Classification Based on Deep Neural Network (DNN) Algorithm and Transfer Learning.

Computational intelligence and neuroscience·2021
See all related articles

Related Experiment Video

Updated: Sep 27, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.2K

Research on Multiplayer Posture Estimation Technology of Sports Competition Video Based on Graph Neural Network

Xiaoping Guo1

  • 1Shaanxi Normal University, Xi'an, Shaanxi 710000, China.

Computational Intelligence and Neuroscience
|April 11, 2022
PubMed
Summary

This study introduces a novel graph neural network approach for accurate human pose estimation in sports videos. The method effectively addresses limitations of traditional techniques, improving multi-person pose analysis in dynamic game footage.

More Related Videos

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.4K
Measuring Engagement of Spectators of Social Digital Games
14:02

Measuring Engagement of Spectators of Social Digital Games

Published on: July 3, 2021

3.6K

Related Experiment Videos

Last Updated: Sep 27, 2025

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.2K
Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease
10:28

Dynamic Digital Biomarkers of Motor and Cognitive Function in Parkinson's Disease

Published on: July 24, 2019

15.4K
Measuring Engagement of Spectators of Social Digital Games
14:02

Measuring Engagement of Spectators of Social Digital Games

Published on: July 3, 2021

3.6K

Area of Science:

  • Computer Vision
  • Sports Analytics
  • Machine Learning

Background:

  • Traditional sports video analysis relies on manual annotation, which is costly and limited.
  • Existing methods using manual features for human pose detection lack accuracy, especially with occlusions.

Purpose of the Study:

  • To develop an advanced human pose detection method for sports videos.
  • To improve the accuracy and efficiency of multi-person pose estimation in sports competitions.

Main Methods:

  • Adapted a neural network, integrating local and global features inspired by Deep-ID.
  • Combined the improved neural network with a human joint model.
  • Developed a graph neural network-based approach for human pose detection.

Main Results:

  • The proposed algorithm demonstrates superior human posture estimation in sports videos.
  • Achieved strong performance in multi-person pose estimation tasks within sports game footage.

Conclusions:

  • The graph neural network-based method offers a significant improvement over traditional approaches.
  • This technique is effective for analyzing complex human poses in dynamic sports environments.