We have for long researched sports technology, both for distributing the video of live broadcasts and managing the archives in Norway and Sweden. We develop systems, from camera capture to dissemination (shown in the image), that are actively used and tested on real users, where the users can see highlights and summaries, get recommendations, collect favorite events, make personalized playlists, etc. However, there are a lot of open questions and issues to address like how to make (usually automated, AI-based) ...
- event detection systems (can we locate where a particular event is in the video, understand the semantics, e.g., detect a goal, a penalty, a booking, a shot, a drible, a tackle, etc.)
- clipping systems (find the best start and stop for a video clip of an event to capture the best beginning and ending, e.g., find good clipping points for example not in the midle of a replay)
- object tracking (for many tasks, it is important to track object like players, ball/puck, referee, sponsor logos, etc. For example, you want to clip a video tracking the ball or a particular player, or you want to show a sponsor how often their logo has been exposed to the viewers.)
- video shot classification (classify the different shot and camera angles, e.g., is this the first goal sequence, a replay, players cheering, a close-up, a zoomed-out, the fans, etc. Such information is important when summarizing and clipping a video sequence consisting of multiple camera shots)
- video and/or text summarization systems (how can we create a compilation of the main events of a video and create a highlight package like shown on the sport news, e.g., make automatic game highlight for the news or automatically write a blog post)
- gamification solutions for users (e.g., functions to engage the fans) like video-based quiz-systems, poll and voting systems, etc.
- cropping systems (videos are usually recorded in a wide-screen format by the broadcasters targeting traditional TV devices, but people today often consume video on their phones on portrait format (standing, social media apps), and a question is how to capture the essence of a video to fit the new screen format, e.g., resize images and videos to match target devices and applications, for example going from a 16:9 TV format to a 1:1 Instagram format)
- video search engines (video sites like YouTube contain a lot of information, but how can you find a particular single event. For example, football sites usually have 10.000s of goals. Can we make a search engine based on both existing metadata and spoken audio in the videos to make an efficient search?)
Each of these points can be separate master topics or can be combined. Or do you have a related idea yourself that can help improve current video systems?
We collaborate with the leagues and elite clubs in Norway and Sweden, the football associations, Telenor, broadcasters, Forzasys (a streaming technology company), Telenor and several international partners. In addition, we collaborate with the Swedish Hockey League, and are entering sports like cricket, horse jumping, basketball and tennis. So, the possibilities are many!!
Want to be part of our research group and improve the current systems? Contact us, and let’s see if we can find a thesis topic that matches your interests!
What do you learn:
- video analysis
- machine learning / AI
- user studies
- building systems
Qualifications:
- Hard working, motivated
- Interested in learning (the rest can be learned during the thesis work)
For more information and examples, see for example:
- https://fotbollplay.se
- https://forzasys.com
Contacts:
Pål Halvorsen <paalh@ifi.uio.no>, <paalh@simula.no>
Michael Riegler <michael@simula.no>