[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3306307.3328148acmconferencesArticle/Chapter ViewAbstractPublication PagessiggraphConference Proceedingsconference-collections
invited-talk

Visualization of putting trajectories in live golf broadcasting

Published: 28 July 2019 Publication History

Abstract

We developed a system for visualizing golf putting trajectories that can be used in live broadcasting. The trajectory computer graphics (CGs) in a golf putting scene are useful for visualizing the results of past plays and the shape of the green. In addition, displaying past trajectories that were shot near the position of the next player helps TV viewers predict the ball movement of the next play. Visualizing the putting trajectories in this way offers TV viewers a new style of watching live golf tournaments and helps make the programs more understandable and exiting.

Supplementary Material

ZIP File (a37-takahashi.zip)
Supplemental material.
MP4 File (a37-takahashi.mp4)
MP4 File (gensub_175.mp4)

References

[1]
B. Babenko, M. H. Yang, and S. Belongie. 2011. Robust object tracking with online multiple instance learning. In IEEE Trans. Pattern Anal. Mach. Intell. Vol. 33, No. 8. 1619--1632.
[2]
Z. Kalal, K. Mikolajczyk, and J. Matas. 2010. Forward-Backward Error: Automatic Detection of Tracking Failures. In In Proc. of the International Conference on Pattern Recognition (ICPR2010).
[3]
Z. Kalal, K. Mikolajczyk, and J. Matas. 2012. Tracking-learning-detection. In IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol.37, No.7. 1409--1422.
[4]
A. Lukezic, T. Vojir, L. C. Zajc,J. Matas, and M. Kristan. 2018. Discriminative Correlation Filter with Channel and Spatial Reliability. In Proc of the International Conference on Computer Vision (CVPR),. 6309--6318.

Index Terms

  1. Visualization of putting trajectories in live golf broadcasting

    Recommendations

    Comments

    Please enable JavaScript to view thecomments powered by Disqus.

    Information & Contributors

    Information

    Published In

    cover image ACM Conferences
    SIGGRAPH '19: ACM SIGGRAPH 2019 Talks
    July 2019
    143 pages
    ISBN:9781450363174
    DOI:10.1145/3306307
    Permission to make digital or hard copies of part or all 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 third-party components of this work must be honored. For all other uses, contact the Owner/Author.

    Sponsors

    Publisher

    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 28 July 2019

    Check for updates

    Author Tags

    1. live golf broadcasting
    2. machine learning
    3. visual object tracking

    Qualifiers

    • Invited-talk

    Conference

    SIGGRAPH '19
    Sponsor:

    Acceptance Rates

    Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

    Contributors

    Other Metrics

    Bibliometrics & Citations

    Bibliometrics

    Article Metrics

    • 0
      Total Citations
    • 200
      Total Downloads
    • Downloads (Last 12 months)10
    • Downloads (Last 6 weeks)0
    Reflects downloads up to 20 Dec 2024

    Other Metrics

    Citations

    View Options

    Login options

    View options

    PDF

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader

    Media

    Figures

    Other

    Tables

    Share

    Share

    Share this Publication link

    Share on social media