University of Cambridge > Talks.cam > Machine Learning @ CUED > Presenting Hawk-Eye’s Skeletrack: Our machine learning approach to building a real time skeletal tracking system for sports, and how we're using it to shape the future of fan engagement

Presenting Hawk-Eye’s Skeletrack: Our machine learning approach to building a real time skeletal tracking system for sports, and how we're using it to shape the future of fan engagement

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Dr R.E. Turner.

Imagine you’re sitting at home watching your favourite sport and you think the manager or referee makes a bad decision. But instead of shouting at the tv, you just rewind and watch a virtual replay of what would have happened if the decision had been different. Well in the not too distant future, you might be able to do just that. Over the past few years at Hawk-Eye Innovations, we have been developing a state of the art, real time, 3D, skeletal tracking system that has the potential to not only revolutionise sports adjudication, analytics and fan engagement, but also provide us with streams of tracking data, unlocking a whole host of opportunities for R&D in Machine Learning. This talk will cover how we have built Skeletrack from the ground up using machine learning as well as it’s current applications (including Semi-Automatic Offside at the FIFA World Cup), the types of approaches and problems we see day to day within the Machine Learning team at Hawkeye, and finally the project that we are currently working on with Cambridge University that will one day put you in the manager’s shoes.

Here’s a short video if you want to see Skeletrack in action: https://www.youtube.com/watch?v=slVEXt7Jfxk

This talk is part of the Machine Learning @ CUED series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2024 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity