Research on Face Recognition Sports Intelligence Training Platform Based on Artificial Intelligence

被引:4
作者
Yang, Jie [1 ]
Tang, Lian [1 ]
Li, Xin-Wei [1 ]
机构
[1] Hunan Inst Engn, Dept Phys Educ, 88 Fuxing East Rd, Xiangtan, Hunan, Peoples R China
关键词
Sports; artificial intelligence; face recognition; convolutional neural network;
D O I
10.1142/S0218213021400157
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the application of artificial intelligence in many social fields, the research of human behavior recognition and non-contact detection of human physiological parameters based on face recognition and other technologies has developed rapidly, and the application of artificial intelligence in culture, sports and entertainment has also begun to rise. How to apply the existing mature technology to the sports intelligence training system taking table tennis as an example is a hot issue worthy of study. In this paper, a comprehensive intelligent table tennis training system and platform based on Convolutional Neural Network face recognition and face heart rate detection is designed, which is mainly used to solve the philosophical training problem in table tennis. In the system place, an identification cameras is set at the entrance of table tennis training places, which is used for table tennis players' sign-in and training table number allocation, and an intelligent analysis cameras is set above each intelligent training table, which is used for detecting the face and heart rate of table tennis players. Each intelligent training platform consists of intelligent voice control unit, server, camera, industrial control computer, monitor and other terminal modules. The member data center constitutes the platform of intelligent table tennis training system.
引用
收藏
页数:21
相关论文
共 20 条
  • [1] 2D Human Pose Estimation: New Benchmark and State of the Art Analysis
    Andriluka, Mykhaylo
    Pishchulin, Leonid
    Gehler, Peter
    Schiele, Bernt
    [J]. 2014 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2014, : 3686 - 3693
  • [2] Holistic big data integrated artificial intelligent modeling to improve privacy and security in data management of smart cities
    Chen, Jie
    Ramanathan, L.
    Alazab, Mamoun
    [J]. MICROPROCESSORS AND MICROSYSTEMS, 2021, 81
  • [3] Chen Z., 2015, Comput. Sci., V53, P68
  • [4] ECO: Efficient Convolution Operators for Tracking
    Danelljan, Martin
    Bhat, Goutam
    Khan, Fahad Shahbaz
    Felsberg, Michael
    [J]. 30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, : 6931 - 6939
  • [5] Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual Tracking
    Danelljan, Martin
    Robinson, Andreas
    Khan, Fahad Shahbaz
    Felsberg, Michael
    [J]. COMPUTER VISION - ECCV 2016, PT V, 2016, 9909 : 472 - 488
  • [6] Pictorial structures for object recognition
    Felzenszwalb, PF
    Huttenlocher, DP
    [J]. INTERNATIONAL JOURNAL OF COMPUTER VISION, 2005, 61 (01) : 55 - 79
  • [7] REPRESENTATION AND MATCHING OF PICTORIAL STRUCTURES
    FISCHLER, MA
    ELSCHLAGER, RA
    [J]. IEEE TRANSACTIONS ON COMPUTERS, 1973, C 22 (01) : 67 - 92
  • [8] Gao J., 2020, IEEE Transactions on Services Computing
  • [9] Analysis of a complex of statistical variables into principal components
    Hotelling, H
    [J]. JOURNAL OF EDUCATIONAL PSYCHOLOGY, 1933, 24 : 417 - 441
  • [10] PoseTrack: Joint Multi-Person Pose Estimation and Tracking
    Iqbal, Umar
    Milan, Anton
    Gall, Juergen
    [J]. 30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017), 2017, : 4654 - 4663