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Reading Time
3 minutes
Vadim Zubkov
Project Manager at OpenCV.ai
AI in Tennis: Elevating the Game with Computer Vision Technology
Applied AI #2. Revolutionizing Tennis with AI and Computer Vision
At OpenCV.ai, we have been developing cutting-edge AI-based analytic algorithms for tennis, aiming to reshape the way professional athletes train and perform in various sports. The growing influence of AI in the sports industry has led to significant advancements in training methods and analytics, providing invaluable insights for athletes and coaches alike. Here, we break down the key benefits and applications of AI and Computer Vision in tennis, showcasing our expertise in this domain.
May 10, 2023
Ball Movement Analysis: Trajectory, Speed, and Impact
The foundation of AI-based analytics in tennis lies in the analysis of ball movement. By leveraging AI algorithms, we can track the ball's trajectory, speed, and even the exact moments when it hits the racket or the court. These insights allow athletes to refine their techniques and keep track of important details. The resulting visualizations such as the color-coded trajectory of the ball can ultimately lead to improved performance.
Player Movement Analysis: Perfecting Techniques with 3D Models
Another crucial aspect of AI and computer vision in tennis is the analysis of player movement. By using multiple calibrated cameras positioned around the court, we can capture different angles of the athlete during training. This data is then used to estimate 3D keypoints on the player's body (such as shoulders, elbows, wrists, and head position), creating a 3D model that provides valuable insights into their unique playing style and areas for improvement.
These analytics enable athletes and coaches to review videos and 3D skeletons based on the collected data, ultimately leading to more efficient training and better performance on the court.
Court Geometry Analysis: Understanding the Playing Field
Analyzing the court's geometry is another essential component of AI and computer vision in tennis. By detecting the court's lines and boundaries, as well as any restricted areas, we can better understand the playing field and help athletes refine their strategies.
When combined with ball and player movement analysis, this comprehensive understanding of the game's dynamics allows for more effective decision-making and training improvements.
The Future of Tennis Training: Harnessing AI and Computer Vision
The integration of AI and Computer Vision in tennis training has already proven to be a game-changer. By providing detailed insights into ball movement, player positioning, and court geometry, our advanced analytic algorithms have begun to revolutionize the way athletes train and compete. As AI technology continues to advance, we can expect even greater innovations in sports analytics, pushing the boundaries of human potential and transforming the athletic landscape for generations to come.
Computer vision technology is making its way into tennis, acting as a line arbiter. Coaches now use artificial intelligence to spot patterns that humans cannot see. AI is capable of quickly layering data to detect areas of significance. AI also accelerates media coverage of tennis tournaments, creating video content in seconds and making match highlights and smart playlists available to fans almost immediately after a match.
Conclusion
At OpenCV.ai, we are proud to be at the forefront of this transformation, and we are committed to driving the adoption of AI and Computer Vision technologies in sports and beyond. Our expertise and innovative solutions aim to empower athletes and coaches with the tools they need to excel in today's highly competitive sports environment.
Computer Vision in Sports: People Train and Compete — Machines Watch and Help
At the upcoming 2024 Olympic Games in Paris, the world will see the most advanced AI and computer vision systems for sports developed by Intel. These systems will not only help capture athletic performance with millimeter and millisecond accuracy but also create 3D models of athletes for replays and analyzing complex situations. The data and models will be available to both referees and spectators.
Artificial intelligence and computer vision systems in sports are no longer a high-tech novelty but an everyday reality. People train, challenge, and watch others compete — and hundreds of tech companies are helping to make it safer and more efficient. And more fun, too!
April 16, 2024
Which GPUs are the most relevant for Computer Vision
In the field of CV, selecting the appropriate hardware can be tricky due to the variety of usable machine-learning models and their significantly different architectures. Today’s article explores the criteria for selecting the best GPU for computer vision, outlines the GPUs suited for different model types, and provides a performance comparison to guide engineers in making informed decisions.
April 12, 2024
Digest 19 | OpenCV AI Weekly Insights
Dive into the latest OpenCV AI Weekly Insights Digest for concise updates on computer vision and AI. Explore OpenCV's distribution for Android, iPhone LiDAR depth estimation, simplified GPT-2 model training by Andrej Karpathy, and Apple's ReALM system, promising enhanced AI interactions.
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