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Department of Computer Science
Fixed-term for a maximum of 11 months, to end no later than 31 July 2020.
Project Title: Automated player performance event detection in football video
Performance analysis is a vital part of the modern game in football, allowing coaches, sports scientists and players to capture data that can inform decision-making and optimise performance. Loughborough University - the world's No.1 university for sports-related studies and a centre of excellence for research in science and technology - is working with sport tech innovator Statmetrix Ltd to provide an exciting new performance analysis solution.
We are seeking a highly motivated individual with relevant skills to join the project team.
About the project
Capturing accurate player performance data is essential for match analysis and can have a huge impact on player and team performance. However, existing player performance analysis often relies on the manual logging of a large amount of 'action events' (e.g. ball passing, shots), action locations and their results (successful or not). Such detailed data is currently obtained by watching every game video - which is both time-consuming and prone to human judgement and errors.
The goal of this project is to explore the use of cutting-edge computer vision/deep learning technology to detect and track both the players and the football, recognising body limbs, and deriving accurate performance-relevant game event and motion data (e.g. running, kicking, passing) for football player analytics.
Funded by Innovate UK, the project sees Loughborough University and Statmetrix Ltd working together to develop a solution that will close the gap for automated sports video analytics. Statmetrix Ltd is an innovative sports technology company, providing a sound commercial proposition and route to market of this solution.
About the Research Associate role
You will join one of the UK's Top-10 research-led universities (REF 2014) and a highly-ranked Computer Science department with access to a wide range of facilities including HPC, high-spec deep learning machines, computer vision software platforms, and various cameras and embedded systems, as well as essential training.
The successful candidate will be a motivated individual ideally in possession of practical experience in deep learning, computer vision, and human motion analysis from videos/ images with a PhD/MSc degree or equivalent in these fields. Programming skills in Python, C/C++ and relevant packages are highly desirable.
The post holder will work within the Department of Computer Science under the supervision of Dr Li and Prof. Meng. You will also closely work with other academics, researchers and software engineers in the project consortium from both Loughborough University and industry partner Statmetrix.
Closing date for applications: 5 July 2019.
Informal enquiries should be made to Dr Baihua Li, by email at B.Li@lboro.ac.uk
For further details please follow this link.