Athletes' throwing action recognition method based on PCA-LBP algorithm

被引：1
|
作者：
Liu, Yingjie [1 ]
机构：
[1] School of Physical Education, Shangqiu Normal University, Shangqiu,476000, China
来源：
International Journal of Computational Intelligence Studies | 2023年 / 12卷 / 1-2期
关键词：
Motion estimation - Sports;
D O I：
10.1504/IJCISTUDIES.2023.132493
中图分类号：
学科分类号：
摘要：
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. © 2023 Inderscience Enterprises Ltd.
引用
收藏
页码：130 / 141
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