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AI-Sports '21: 2nd International Workshop on Artificial Intelligence in Sports

In conjunction with the IEEE International Conference on Multimedia and Expo (ICME) 2021

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  • Organizers
  • Huang-Chia Shih, Rainer Lienhart, Takahiro Ogawa, Thomas B. Moeslund, Jenq-Neng Hwang

  • Descriptions
  • Utilization of various sensors for bioinformatics data acquisition has become increasingly popular in recent years. Meanwhile, research fields like computer vision, sensing technology, wearable technology, machine learning and data-driven approaches recently made huge advancements and have massively impacted many aspects of sports, the joint assessment of multiple modalities for sport data analytics offers appealing innovations to advance the field. Data-driven machine learning technique plays an important role in developing and improving sports in recent years. Coaches and athletes are able to utilize this data to make better decisions for developing their team. Popular sports like football fuel the drive for technological advances in AI and machine learning. With the current technology, specific details and strategies can be extracted from the data to help coaches and players see the whole picture with clarity. By adding context to the collected data, coaches and analysts can allocate more time towards developing strategies. The growing number of potential programs shows promising technological advances in the sports industry, but limits are becoming more obvious. There is not enough data to effectively create learning and artificial intelligence. Sporting research has already gone underway by big companies like Google and Facebook. It is apparent that big data sports analytics is a strong, positive correlation to maximizing a sport teamˇ¦s potential, and any team will find themselves at a severe disadvantage if they do not actively incorporate themselves with big data analytics.

  • Scope and Topics
  • This workshop is open to anyone interested in sports content analytics. To cover the rapid progress of emerging areas we plan to focus our target field in three topics:

  • Date and time
  • Friday, July 9, 2021 14:00 UTC+8.

  • Schedule
  • Session Chairs: Huang-Chia Shih (Yuan Ze University, Taiwan) and Takahiro Ogawa (Hokkaido University, Japan)

    14:0514:35Keynote: Pose Analytics in Real-world Problem SolvingPhokgoan Chioh (CTO,, USA)
    14:3514:50Self-supervised Learning for Human Pose Estimation in SportsKatja Ludwig*, Sebastian Scherer, Moritz Einfalt, and Rainer Lienhart (University of Augsburg, Germany)
    14:5015:05Spatiotemporal-Spectral Graph Convolutional Networks for Skeleton-Based Action RecognitionShuo Chen*, Xinghao Jiang, Tanfeng Sun, and Ke Xu (Shanghai Jiao Tong University, China)
    15:0515:20Swimmer Stroke Rate Estimation From Overhead Race VideoTimothy Woinoski* and Ivan Bajic (Simon Fraser University, Canada)
    15:2015:35Center of Mass Trajectory: An Image Descriptor for Baseball Swing Analysis Based on A Single Low Cost CameraChih-Chieh Fang1, Ching-Hsien Hsu1, Chun-Wen Chiu2, Jung-Tang Kung2, and Huang-Chia Shih* 1
    1(Yuan Ze University, Taiwan), 2 (National Taiwan Sport University, Taiwan).
    15:3515:40Closing remarks

    Previous workshops:

  • 1st AI-Sports20' in conjunction with ICME 2020