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
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
相关论文
共 50 条
  • [1] Plastic surgery face recognition using LBP and PCA algorithm
    Dadure, Pankaj
    Sikder, Sayan
    Sambyo, Koj
    2018 2ND INTERNATIONAL CONFERENCE ON ELECTRONICS, MATERIALS ENGINEERING & NANO-TECHNOLOGY (IEMENTECH), 2018, : 49 - 53
  • [2] Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm
    Hongtao Chen
    Zhengbai Lin
    Quan Xu
    Scientific Reports, 15 (1)
  • [3] Recognition method of basketball players' throwing action based on image segmentation
    Zhang, Cong
    Wang, Miao
    Zhou, Limin
    INTERNATIONAL JOURNAL OF BIOMETRICS, 2023, 15 (02) : 121 - 133
  • [4] Face Recognition Based on Fusion Feature of LBP and PCA with KNN
    Zhai, Bo
    Li, Zi-mei
    2018 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL MODELING, SIMULATION AND APPLIED MATHEMATICS (CMSAM 2018), 2018, 310 : 485 - 490
  • [5] Face Recognition Based on LBP and Genetic Algorithm
    Zhao Li-hong
    Liu Fei
    Wang Yong-jun
    PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 1582 - 1587
  • [6] Face Recognition Based On LBP And LNMF Algorithm
    Wu, Menglu
    Lu, Tongwei
    2016 15TH INTERNATIONAL SYMPOSIUM ON PARALLEL AND DISTRIBUTED COMPUTING (ISPDC), 2016, : 368 - 371
  • [7] Face recognition based on improved LBP algorithm
    Shi, Zhi-Yuan
    Lin, Mei-Jia
    Gao, Zhi-Bin
    Wu, Yan-Yang
    Zhang, Hao
    Li, Li-Zhong
    Journal of Computers (Taiwan), 2019, 30 (04) : 122 - 129
  • [8] Facial expression recognition based on fusion feature of PCA and LBP with SVM
    Luo, Yuan
    Wu, Cai-ming
    Zhang, Yi
    OPTIK, 2013, 124 (17): : 2767 - 2770
  • [9] Acquisition and recognition method of throwing information for shot-put athletes
    Gao, Zhen
    Shen, Huanghuan
    Xie, Shuangwei
    Lei, Jianhe
    Zhang, D.
    Ge, Yunjian
    ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF THEORETICAL AND METHODOLOGICAL ISSUES, 2007, 4681 : 1050 - +
  • [10] An effective recognition method of breast cancer based on PCA and SVM algorithm
    Liu, Jihong
    Ma, Weina
    MEDICAL BIOMETRICS, PROCEEDINGS, 2007, 4901 : 57 - 64