short-paper

Badminton Video Analysis based on Spatiotemporal and Stroke Features

Authors:

Samuel SitumeangAuthors Info & Claims

ICMR '17: Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

Pages 448 - 451

https://doi.org/10.1145/3078971.3079032

Published: 06 June 2017 Publication History

Abstract

Most of the broadcasted sports events nowadays present game statistics to the viewers which can be used to design the gameplay strategy, improve player's performance, or improve accessing the point of interest of a sport game. However, few studies have been proposed for broadcasted badminton videos. In this paper, we integrate several visual analysis techniques to detect the court, detect players, classify strokes, and classify the player's strategy. Based on visual analysis, we can get some insights about the common strategy of a certain player. We evaluate performance of stroke classification, strategy classification, and show game statistics based on classification results.

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Cited By

Zhang JHan DHan SLi HLam WZhang M(2025)ChatMatchComputer Speech and Language10.1016/j.csl.2024.10169489:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.csl.2024.101694
Lien YLian CWang Y(2025)ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flowsMachine Learning10.1007/s10994-024-06682-0114:2Online publication date: 27-Jan-2025
https://doi.org/10.1007/s10994-024-06682-0
Yue SParamesran RKrishnasamy G(2024)Ready-to-Serve Detection in Badminton Videos2024 International Conference on Electronics, Information, and Communication (ICEIC)10.1109/ICEIC61013.2024.10457177(1-5)Online publication date: 28-Jan-2024
https://doi.org/10.1109/ICEIC61013.2024.10457177
Show More Cited By

Index Terms

Badminton Video Analysis based on Spatiotemporal and Stroke Features
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision tasks
        Activity recognition and understanding
2. Human-centered computing
  1. Visualization
    1. Visualization application domains
      1. Visual analytics

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Information

Published In

cover image ACM Conferences

ICMR '17: Proceedings of the 2017 ACM on International Conference on Multimedia Retrieval

June 2017

524 pages

ISBN:9781450347013

DOI:10.1145/3078971

General Chairs:
Bogdan Ionescu
University Politehnica of Bucharest, Romania
,
Nicu Sebe
University of Trento, Italy
,
Program Chairs:
Jiashi Feng
National University of Singapore, Singapore
,
Martha Larson
Radboud University & Delft University of Technology, The Netherlands
,
Rainer Lienhart
University of Augsburg, Germany
,
Cees Snoek
University of Amsterdam & Qualcomm Research Netherlands, The Netherlands

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

SIGMM: ACM Special Interest Group on Multimedia

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 June 2017

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Short-paper

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Ministry of Science and Technology, Taiwan

Conference

ICMR '17

Sponsor:

SIGMM

ICMR '17: International Conference on Multimedia Retrieval

June 6 - 9, 2017

Bucharest, Romania

Acceptance Rates

ICMR '17 Paper Acceptance Rate 33 of 95 submissions, 35%;

Overall Acceptance Rate 254 of 830 submissions, 31%

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Citations

Cited By

Zhang JHan DHan SLi HLam WZhang M(2025)ChatMatchComputer Speech and Language10.1016/j.csl.2024.10169489:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.csl.2024.101694
Lien YLian CWang Y(2025)ShuttleFlow: learning the distribution of subsequent badminton shots using normalizing flowsMachine Learning10.1007/s10994-024-06682-0114:2Online publication date: 27-Jan-2025
https://doi.org/10.1007/s10994-024-06682-0
Yue SParamesran RKrishnasamy G(2024)Ready-to-Serve Detection in Badminton Videos2024 International Conference on Electronics, Information, and Communication (ICEIC)10.1109/ICEIC61013.2024.10457177(1-5)Online publication date: 28-Jan-2024
https://doi.org/10.1109/ICEIC61013.2024.10457177
Ibh MGraßhof SHansen D(2024)A stroke of genius: Predicting the next move in badminton2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00342(3376-3385)Online publication date: 17-Jun-2024
https://doi.org/10.1109/CVPRW63382.2024.00342
Li QChiu THuang HSun MKu W(2024)VideoBadminton: A Video Dataset for Badminton Action Recognition2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825009(1387-1392)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825009
Yu JLiu YWei HXu KCao YLi J(2024)Towards Highly Effective Moving Tiny Ball Tracking via Vision TransformerAdvanced Intelligent Computing Technology and Applications10.1007/978-981-97-5588-2_31(368-379)Online publication date: 13-Aug-2024
https://doi.org/10.1007/978-981-97-5588-2_31
Jain AAgrawal SChauhan GShruti ISingh P(2024)Badminton Shot Recognition with LSTM NetworkThe Future of Artificial Intelligence and Robotics10.1007/978-3-031-60935-0_28(307-315)Online publication date: 20-Aug-2024
https://doi.org/10.1007/978-3-031-60935-0_28
Schlenger JWunderlich FRaabe DMemmert D(2023)Systematic Analysis of Position-Data-based Key Performance IndicatorsInternational Journal of Computer Science in Sport10.2478/ijcss-2023-000622:1(80-101)Online publication date: 16-Jun-2023
https://doi.org/10.2478/ijcss-2023-0006
Chen WWu HShih YWang CWang Y(2023)Exploration of Player Behaviours from Broadcast Badminton VideosComputer Graphics Forum10.1111/cgf.1478642:6Online publication date: 6-Mar-2023
https://doi.org/10.1111/cgf.14786
Zhang YLiu RYang YGao SLi J(2023)An Online Recognition Method of Badminton Stroke Based on Inertial Sensor2023 3rd International Conference on Computer, Control and Robotics (ICCCR)10.1109/ICCCR56747.2023.10193896(75-81)Online publication date: 24-Mar-2023
https://doi.org/10.1109/ICCCR56747.2023.10193896
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