Tag Archives: Wimbledon 2019

How Wimbledon and Watson use AI to edit autofocus for video (Part 2)

Applications of AI in Wimbledon

To do this, AI analyzes factors such as gestures and players’ reactions (such as punches on the air celebrating and greeting by touching two fists on each other) and listening to the sound of the crowd, like exhaling and cheering. For the highlights of Wimbledon 2019, IBM said it trained Watson to take advantage of more acoustical data, such as detecting every shot of the ball – making automatic cropping of match highlights closer around the main activities in the innings and can also help determine the series of pay backs.

Misleading AI

Of course, there are problems with deviations in the AI ​​we face for a long time. Wimbledon has many situations that lead to fooling the automated system – the center of the stadium will have more fans (and therefore more noise), while a superstar like Roger Federer might have many fans, creating more cheering sounds than the 89-ranked players in the world. To detect the best action, regardless of these external factors, IBM trained Watson to better identify trends and patterns in acoustics – creating a fourth type of data point to reduce risk of deviation.

This result is enabled via AI OpenScale. IBM launched the AI ​​OpenScale last year, providing a set of automated detection and mitigation tools – constantly monitoring bias-based decision-making based on AI applications. Specifically, for Wimbledon, this technology helps Watson plan to “learn” the overall crowd noise and use it as a neutral mechanism, from which other heights will be measured based on that basic measure.

Ace Index (to score the goal directly)

During the production of video accents, Watson also exploited match statistics for more context. These statistics are created by tennis players (usually players at the district level). They are people who are hired to sit next to the stage to identify subjective data points such as unforced error, other statistical information – such as handing the ball directly or double errors – and important moments in tennis matches, such as points that bring break points, set points, match points.