[Feature Story] Technology on the Prize: Computer Vision in the Olympic Games

by Shu-Yu Liu

The Tokyo 2020 Olympic Games had attracted the attention of audience from around the world. In addition to the exciting competitions, there was the use of technology by athletes and coaches from a statistical and strategic perspective, where computer vision can be applied to the games.

“In”- result determined by the Hawkeye challenge of the match point

Taiwanese badminton duo Lee Yang and Wang Chi-lin won the gold medal in the Tokyo Olympics men’s doubles final. In response to the challenging raised by the opposing team, the Hawkeye review showed the shuttlecock falling to the baseline and a line call was displayed indicating that it was “in” for the Taiwanese team.

In the games, players are given opportunities to challenge a call, and on the screen shows the computer simulation processed using computer vision. The Hawkeye system often seen in tennis, badminton, and volleyball features a number of high-speed cameras that track the trajectory of the ball. A computer system then processes the volume and weight of the ball as well as field wind speed to generate a three-dimensional image on the screen. The flight path and where the ball lands shown are the result of computer simulation, instead of the slow-motion images post-processed by computer.

The Hawkeye system was developed by the British engineer Paul Hawkins using optical photography, AI, and computer vision. The system is able to track and display the path of the ball and even predict the future path.

Hawkeye equipped with high-speed cameras to track the trajectory of the ball

AI coaching for the players

Taiwanese weightlifter Kuo Hsing-chun bags first gold for Taiwan at the Tokyo Olympic Games. The moment she completed her movement on stage, the science team back in Taiwan used the AI coaching system to analyze the images from the broadcast and to generate body models for feedback on the body angles, the speed of barbell movements, and other information. The data can be sent back to the coach on-site for reference.

Precision Weightlifting, a project by the Ministry of Science and Technology (MOST) makes use of image recognition and AI technology for the development of a system to track the barbell trajectory and athletes’ exertion by. From these readings, trainers can tell if the athletes are exhausted, based on which the training intensities can be adjusted. With the AI systems, information on the opponents in the game can also be collected for analysis of their strengths and weaknesses. These results can be sent to the coaches in the games to make real-time decisions for better strategies.

Real-time information by AI coaching system for athletes in the games

Conclusion

Powerful technology such as computer vision is now introduced into sports to help athletes make decision and correct their movements. Although experience that develops over time is important, the use of technology does come in handy for athletes and their coaches not only during training but in the competition.

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