Computing Run-out Decisions Using Object Detection and Support Vector Machine Algorithm

In the game of cricket, there are various kinds of dismissals that can be caused due to multiple reasons. Few of them include the bowler’s brilliance and the batsman’s mistake. Run-out being one kind of dismissal, that completely changes the fortune and momentum of teams. Most of the time, it becomes difficult for the on-field umpire to give a judgement on run-out with naked eyes. So, the decisions are transferred to the third umpire, who gives the final decision based on a time-consuming technique. Therefore, we are proposing an approach, in which dismissal prediction is made using object detection and support vector machine. As the dismissal prediction is made based on images from different angles from various cameras, we were successful in achieving an accuracy rate of 87%. Additionally, since it works on an automated process, it is much more time-efficient than the traditional system. Thus by using this approach, errors are minimized and machine learning capabilities are provided to decision making in the game of cricket.