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 Experiment Video

Updated: Jun 6, 2025

Comparison of Kinetic Characteristics of Footwork during Stroke in Table Tennis: Cross-Step and Chasse Step
07:19

Comparison of Kinetic Characteristics of Footwork during Stroke in Table Tennis: Cross-Step and Chasse Step

Published on: June 16, 2021

2.6K

Fast moving table tennis ball tracking algorithm based on graph neural network.

Tianjian Zou1, Jiangning Wei1, Bo Yu1

  • 1School of Artificial Intelligence, Beijing University of Post and Telecommunications, XiTuCheng Road, 10, Haidian, 100082, Beijing, China.

Scientific Reports
|November 26, 2024
PubMed
Summary

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

Stratified polymer brushes from microcontact printing of polydopamine initiator on polymer brush surfaces.

Macromolecular rapid communications·2014
Same author

Distinct morphological features of ruptured culprit plaque for acute coronary events compared to those with silent rupture and thin-cap fibroatheroma: a combined optical coherence tomography and intravascular ultrasound study.

Journal of the American College of Cardiology·2014
Same author

The ABI4-induced Arabidopsis ANAC060 transcription factor attenuates ABA signaling and renders seedlings sugar insensitive when present in the nucleus.

PLoS genetics·2014
Same author

Evaluation of global longitudinal strain of left ventricle and regional longitudinal strain in the region of left ventricular leads predicts the response to cardiac resynchronization therapy in patients with ischemic heart failure.

Cell biochemistry and biophysics·2014
Same author

Exosomes derived from mesenchymal stem cells.

International journal of molecular sciences·2014
Same author

Association of apolipoprotein E polymorphism with maximal oxygen uptake after exercise training: a study of Chinese young adult.

Lipids in health and disease·2014
Same journal

Peripheral B-cell receptor repertoire predicts immune-related adverse events following immune checkpoint inhibitor therapy in advanced renal cell carcinoma.

Scientific reports·2026
Same journal

Effects of black soldier fly (Hermetia illucens L.) larvae zoocompost on the mineral element content of blue honeysuckle berries.

Scientific reports·2026
Same journal

Investigation on absorption refrigeration performance of R1243zf with imidazolium ionic liquid as the working pairs.

Scientific reports·2026
Same journal

DeepTriage-CN: integrating clinical text with vital signs for emergency department admission prediction in an aging population.

Scientific reports·2026
Same journal

Gold nanoparticles as dual-action antiviral agents: disruption of SARS-CoV-2 viral envelopes and RNA integrity.

Scientific reports·2026
Same journal

Comparison of capillary microsampling and venous blood for multi-pathogen serosurveillance.

Scientific reports·2026
See all related articles
This summary is machine-generated.

This study introduces a novel method for tracking table tennis balls in videos, overcoming challenges posed by their small size and fast movement. The new approach enhances sports analysis by improving object detection and tracking accuracy.

Area of Science:

  • Computer Vision
  • Sports Analytics
  • Machine Learning

Background:

  • Object tracking in sports video analysis is crucial for understanding techniques and tactics.
  • Tracking small, fast-moving objects like table tennis balls presents significant challenges for existing algorithms.
  • Current methods often fail to meet the demands of real-world sports applications.

Purpose of the Study:

  • To develop an effective method for detecting and tracking table tennis balls in video footage.
  • To address the limitations of current object tracking algorithms in dynamic sports environments.
  • To improve the accuracy and scalability of sports video analysis for table tennis.

Main Methods:

  • A combined approach integrating detection and discrimination tailored for table tennis ball motion.
Keywords:
Fast moving objectGraph neural networkObject detectionObject trackingSports analyticsTable tennis

More Related Videos

A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

14.8K
Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.4K

Related Experiment Videos

Last Updated: Jun 6, 2025

Comparison of Kinetic Characteristics of Footwork during Stroke in Table Tennis: Cross-Step and Chasse Step
07:19

Comparison of Kinetic Characteristics of Footwork during Stroke in Table Tennis: Cross-Step and Chasse Step

Published on: June 16, 2021

2.6K
A Protocol for Real-time 3D Single Particle Tracking
10:16

A Protocol for Real-time 3D Single Particle Tracking

Published on: January 3, 2018

14.8K
Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut
08:32

Tracking Rats in Operant Conditioning Chambers Using a Versatile Homemade Video Camera and DeepLabCut

Published on: June 15, 2020

12.4K
  • Refinement of a common video differential detector for object identification.
  • Introduction of a Graph Max-message Pass Neural Network (GMP) for object discrimination and tracking.
  • Enhancement of an existing dataset with diverse scenarios for robust model training.

    • Main Results:

    • The proposed technical solution demonstrates impressive performance on both the enhanced dataset and real-world environments.
    • The algorithms show good scalability, indicating potential for broader applications.
    • The method effectively addresses the challenges of tracking small, fast-moving objects in sports videos.

    Conclusions:

    • The integrated detection and GMP discrimination approach offers a robust solution for table tennis ball tracking.
    • The enhanced dataset and refined algorithms contribute to advancing sports analytics.
    • The developed models show promise for real-time sports analysis and can be adapted to other similar tracking tasks.