Research on Movement Analysis and Guidance in Dance Learning Based on Data Mining

被引:1
|
作者
Yin, Guangle [1 ]
Liu, Jing [1 ]
机构
[1] Henan Polytech, Mus Acad, Zhengzhou 450046, Peoples R China
关键词
All Open Access; Gold; Green;
D O I
10.1155/2022/9327442
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
In dance, we must understand the essential meaning of dance movements from the inside and express them on the basis of dance. Therefore, in the process of developing new dance teaching methods, it is necessary to improve the basic education of dance students, so that they can express the emotions conveyed by dance through body language and movements, and improve dance expression ability. In this context, we made the research and reached the following conclusions: (1) the number of frames of different dance types is also different, and the number of frames to be learned is also increasing. The dance with the highest number of frames is Latin2, which has 3635 frames, and the dance with the highest number of frames that need to be learned is also Latin2, which requires 2519 frames to learn. (2) The data mining method is still the highest among the three methods, and the accuracy of the complete teaching method is 82%, which is the lowest among the three methods, and the accuracy of the decentralized teaching method is 87%. No matter in the test set or the mixed test set, the curve values of deep mining are very stable. First of all, human movements emphasize that in dance, the essential meaning of dance movements needs to be understood from the inside and expressed through the foundation of dance. Therefore, when developing new dance teaching methods, it is necessary to strengthen the basic dance training of students so that students can express the emotions conveyed by dance through body language and movements and improve their dance expression ability. We conduct research in this ecological environment. Different types of dance learning process using different frames, different types of dance in the algorithm transport have different recognition methods, using better and different algorithms can achieve the best performance. Both groups in the Hip Hop dance had a shorter average learning time than both groups in the Latin dance.
引用
收藏
页数:9
相关论文
共 50 条
  • [21] Hand Movement Recognition and Analysis Based on Deep Learning in Classical Hand Dance Videos
    Cai, Xingquan
    Lu, Qingtao
    Li, Fajian
    Liu, Shike
    Hu, Yan
    ADVANCES IN COMPUTER GRAPHICS, CGI 2023, PT III, 2024, 14497 : 53 - 64
  • [22] A transportation guidance system based on data mining and GABP
    Li, Zhuhao
    Guan, Wei
    MECHANICAL DESIGN AND POWER ENGINEERING, PTS 1 AND 2, 2014, 490-491 : 914 - 919
  • [23] DANCE AS MOVEMENT AND OBJECT OF RESEARCH
    Katarincic, Ivana
    8TH INTERNATIONAL SCIENTIFIC CONFERENCE ON KINESIOLOGY, 2017, : 805 - 807
  • [24] Analysis of web-based learning systems by data mining
    Villegas-Ch, W.
    Lujan-Mora, S.
    Buenano-Fernandez, Diego
    Roman-Canizares, M.
    2017 IEEE SECOND ECUADOR TECHNICAL CHAPTERS MEETING (ETCM), 2017,
  • [25] Research and analysis of network data mining based on genetic algorithm
    Shi, Lei
    Zhao, Huiran
    Zhang, Kun
    MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II, 2014, 651-653 : 2181 - 2184
  • [26] The Research of Data Mining Analysis System Based on Pearson relation
    Zhang Hanyun
    Hu Shunfang
    2015 2ND INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND CONTROL ENGINEERING ICISCE 2015, 2015, : 508 - 511
  • [27] Research on technical analysis of basketball match based on data mining
    Kang, Junbiao
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 125 : 109 - 109
  • [28] Research and Analysis of Game Tactics Based on Data Mining Technology
    Zhou Li
    PROCEEDINGS OF THE 2017 5TH INTERNATIONAL CONFERENCE ON MECHATRONICS, MATERIALS, CHEMISTRY AND COMPUTER ENGINEERING (ICMMCCE 2017), 2017, 141 : 280 - 284
  • [29] RETRACTED: Analysis of Main Movement Characteristics of Hip Hop Dance Based on Deep Learning of Dance Movements (Retracted Article)
    Lu, Rui
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [30] Outlier data mining model for sports data analysis based on machine learning
    Yin, Zhimeng
    Cui, Wei
    JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2021, 40 (02) : 2733 - 2742