Abstract
With people paying more attention to health and quality of life, more and more people are keen to exercise through various sports, such as badminton, which is suitable for all ages. With the development of the new era, artificial intelligence and robots have gradually entered people’s lives, among which badminton robot is an intelligent robot that can compete with people in real time. The robot can not only capture and track badminton moving at high speed, but also has a high-speed motion control system to accurately complete the striking action. Therefore, the main research content of this paper is based on badminton robot vision system to capture, identify and analyze badminton players’ striking action. The main research work is as follows: A method of obtaining video segments of badminton striking action according to the flying direction and position of badminton is proposed, and a data set containing 8 kinds of common badminton striking action is made. Then, the dense trajectory algorithm is improved to recognize badminton striking action more effectively. Through the experimental study found that the use of dense trajectory algorithm for badminton players hit action recognition by only extracting the trajectory of feature points in a small range of players reduce the complexity of the algorithm but also enhance the robustness of the algorithm. Through the way of experiments to verify the effectiveness of the non-fixed length trajectory, but also improve the recognition rate of badminton striking action.
Published Version
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