To spotthe backlift, researchers hailing from the University of Johannesburg developed a deep learning computer vision model, utilizing artificial intelligence.
Science is an important aspect of any part of life however it is often neglected when we speak of various type of sports activities. World is changing rapidly and new innovations are pretty handy. Just like GambleUSA is an innovative and trustworthy place to fulfill your gambling needs anytime!
As viewers we often ignore the techniques employed by sportsmen in the excitement to enjoy the each ball of the match. However, ball game is different when you are part of the team’s support staff because they are focused on tiny and more finer details. Most of the spectators are interested in how many runs a batsman made, on the other hand team’s support staff would analyse the batting and bowling techniques and other minute details, taking help from technology for analysis. Even the most precise calculations have a room for mistakes. It is difficult to judge and make assessment of each and every move of the batsmen or bowler even in presence of high quality camera and broadcasting. To avoid these minor faults, researchers are now using artificial intelligence (AI).
During every game of cricket, batsmen need to make quick decision regarding the shot selection while facing a fast bowler because fast bowlers won’t allow much time to think, batsmenthas to make a decision on the backlift – whether he should hit itfor straight or lateral? Now, imagine the technology being improved in a way that it can assist the support staff, or even the players to identify their problem and to come up with solution. In most recent study published in Nature Scientific Reports, researchers from the University of Johannesburg have developed a deep learning computer vision model, using artificial intelligence, that can spot straight backlift batters from lateral ones, using video only.
“This study provides a way forward in the automatic recognition of player patterns and motion capture, making it less challenging for sports scientists, biomechanists and video analysts working in the field,” the report suggests.
This technology will be handy for the coaches. They may be able to give more detailed feedback to players. It can also help identify players with lateral backlift components, like legendary cricketer Sir Donald Bradman who was a pioneer of lateral backlift.
“The beauty of deep learning in AI is that you don’t have to tell the AI what to look for,” said study co-author Tevin Moodley, a doctoral student at the University of Johannesburg.
The researchers found that untrained batters often instinctively use a lateral backlift. “What we have found is that if young players are not coached using traditional methods, they do not pick up the bat straight. They pick the bat up in a lateral direction. This indirectly suggests that a straight backlift is not a natural movement,” said Prof Habib Noorbhai, another author on the article.
