Athletes' throwing action recognition method based on PCA-LBP algorithm Online publication date: Mon, 24-Jul-2023
by Yingjie Liu
International Journal of Computational Intelligence Studies (IJCISTUDIES), Vol. 12, No. 1/2, 2023
Abstract: In order to improve the average recognition rate and accuracy of motion recognition, and improve the recognition effect, a method of athlete throwing motion recognition based on PCA-LBP algorithm is proposed. Kinect device is used to collect motion images, and filter the collected images to reduce the noise contained in the images; LBP method is used to collect the features of the pre processed moving images, obtain the feature codes, and PCA method is used to reduce the dimensions of the extracted motion features. The motion image is segmented to obtain the throwing action area of the athlete, and the action recognition is conducted based on the segmentation results to obtain the throwing action recognition results of the athlete. The analysis of experimental results shows that the method in this paper effectively improves the average recognition rate and recognition accuracy of actions, and the recognition effect is good.
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 Computational Intelligence Studies (IJCISTUDIES):
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