Research on video image face detection and recognition technology based on improved MTCNN algorithm

被引:0
|
作者
Liu J. [1 ]
机构
[1] College of Robotics, Guangdong Polytechnic of Science and Technology, Guangdong Province, Zhuhai
关键词
distinguish; face detection; MTCNN; sample training; video image;
D O I
10.1504/IJWMC.2022.124811
中图分类号
学科分类号
摘要
With the development of modern computer technology and artificial intelligence, face image processing technology has been widely used in people's life and work. In order to realise face image detection and recognition in dynamic video, this paper proposes a face detection and recognition technology based on MTCNN algorithm. MTCNN algorithm includes R-Net, O-net and P-net deep network models, which can realise face image deep processing in dynamic video. In order to train MTCNN algorithm deeply, Wider_Face and CelebA database training sets were used to train the additional test tasks and regression key points of the model. After setting the main parameters of MTCNN algorithm, the algorithm is simulated and analysed. Through the comparative simulation analysis of traditional algorithm, SVM algorithm and 2DPCA algorithm, it can be seen that MTCNN algorithm has more excellent performance and can meet the needs of face image detection and recognition in dynamic video. Copyright © 2022 Inderscience Enterprises Ltd.
引用
收藏
页码:205 / 212
页数:7
相关论文
共 50 条
  • [31] Video Face Detection Based on Improved SSD Model and Target Tracking Algorithm
    Liu, Yilin
    Liu, Ruian
    Wang, Shengxiong
    Yan, Da
    Peng, Bo
    Zhang, Tong
    [J]. JOURNAL OF WEB ENGINEERING, 2022, 21 (02): : 545 - 567
  • [32] RESEARCH for face detection on improved algorithm of AdaBoost
    Chen, Hong
    [J]. 2016 INTERNATIONAL CONFERENCE ON ELECTRONIC, INFORMATION AND COMPUTER ENGINEERING, 2016, 44
  • [33] Image cutting in video media technology application based on detection algorithm
    Xiong, Jiahui
    [J]. INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT, 2023,
  • [34] A Research on Parking Space Detection Algorithm Based on Image Recognition
    Zhu W.
    Huang H.
    Ma J.
    [J]. Qiche Gongcheng/Automotive Engineering, 2019, 41 (07): : 744 - 749and756
  • [35] Research on MTCNN Face Recognition System in Low Computing Power Scenarios
    Xie, YingGang
    Wang, Hui
    Guo, ShaoHua
    [J]. JOURNAL OF INTERNET TECHNOLOGY, 2020, 21 (05): : 1463 - 1475
  • [36] Face Recognition Based on Improved SIFT Algorithm
    Sadeghipour, Ehsan
    Sahragard, Nasrollah
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (01) : 548 - 551
  • [37] An improved face recognition algorithm based on SVD
    Cao, Danyang
    Yang, Bingru
    [J]. 2010 2ND INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING (ICCAE 2010), VOL 3, 2010, : 109 - 112
  • [38] Face recognition based on improved LBP algorithm
    Shi, Zhi-Yuan
    Lin, Mei-Jia
    Gao, Zhi-Bin
    Wu, Yan-Yang
    Zhang, Hao
    Li, Li-Zhong
    [J]. Journal of Computers (Taiwan), 2019, 30 (04) : 122 - 129
  • [39] Face Recognition Technology Based On Image Processing
    Xin, Chen
    Li, Yajuan
    Tian, Zhimin
    [J]. PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MACHINERY, MATERIALS AND COMPUTING TECHNOLOGY, 2016, 60 : 341 - 345
  • [40] An improved algorithm of news video caption detection and recognition
    Yang, Qiang
    [J]. 2011 INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND NETWORK TECHNOLOGY (ICCSNT), VOLS 1-4, 2012, : 1549 - 1552