Arm movement recognition of badminton players in the third hit based on visual search Online publication date: Fri, 05-Aug-2022
by Ling Liu
International Journal of Biometrics (IJBM), Vol. 14, No. 3/4, 2022
Abstract: In order to overcome the problems of low recognition accuracy, high repetition rate of corner points and long recognition time of badminton players' arm movements in the third beat, a new recognition method based on visual search is proposed in this paper. This method uses visual search technology, binocular visual camera to record video, image stabilisation technology to implement histogram equalisation processing on the recorded visual image, and obtains the visual image after noise elimination. This method also uses scale invariant feature conversion algorithm to collect image sift corner features, combines with support vector machine algorithm to construct feature recognition model, and realises the third shot arm movement of badminton players to distinguish. The experimental results show that the signal-to-noise ratio (SNR) of the collected visual images is less than 10 dB, the repetition rate of corners is always lower than 60%, and the recognition time is basically controlled within 0.8 s.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Biometrics (IJBM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook