Design and implementation of full-body motion capture system based on multi-sensor fusion

被引:0
|
作者
Bai, Yan [1 ]
Xi, Jie [1 ]
Liao, Wendong [1 ]
机构
[1] Jiangxi Univ Finance & Econ, Sch Software & Internet Things Engn, Nanchang 330000, Jiangxi, Peoples R China
关键词
sensor; !text type='python']python[!/text; Blende; multi-sensor fusion; motion capture;
D O I
10.1117/12.2615157
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This paper introduces a wearable human motion capture system based on inertial sensor. The sensor nodes are connected by network cables, while the hub node transits data with the computer through Bluetooth. This system not only ensures the data acquisition rate, but also has no movement restrictions for users, such as requiring them to move within a certain range. Using Python programming and Blende engine, the inertial data of each part of the human body is converted into rotation angle and displacement to drive the human model. Meanwhile, rich human-computer interaction functions and visual interface are designed to reduce the difficulty of use. The final motion capture results show that this system has a good performance in recognizing complex human movements, and can be used as a multi-functional motion capture system in motion analysis, film and television production, virtual reality and other fields.
引用
收藏
页数:7
相关论文
共 50 条
  • [1] Modeling a wearable full-body motion capture system
    Einsmann, C
    Quirk, M
    Muzal, B
    Venkatramani, B
    Martin, T
    Jones, M
    [J]. NINTH IEEE INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS, PROCEEDINGS, 2005, : 144 - 151
  • [2] Full-Body Motion Capture-Based Virtual Reality Multi-Remote Collaboration System
    Ha, Eunchong
    Byeon, Gongkyu
    Yu, Sunjin
    [J]. APPLIED SCIENCES-BASEL, 2022, 12 (12):
  • [3] Validation of the Perception Neuron system for full-body motion capture
    Choo, Corliss Zhi Yi
    Chow, Jia Yi
    Komar, John
    [J]. PLOS ONE, 2022, 17 (01):
  • [4] Design and Implementation of Vehicle Chassis Detection System Based on Multi-Sensor Fusion Technology
    Yuan, Dun
    Liu, Lu
    [J]. 2019 4TH INTERNATIONAL CONFERENCE ON ELECTROMECHANICAL CONTROL TECHNOLOGY AND TRANSPORTATION (ICECTT 2019), 2019, : 113 - 116
  • [5] Design and Implementation of Rehabilitation Training and Positioning System Based on Multi-Sensor Information Fusion
    Zhou, Qiuzhan
    Xue, Yongchao
    Chen, Shuozhang
    Zhang, Songling
    Lei, Zongheng
    Si, Yujuan
    [J]. PROCEEDINGS OF THE 2016 4TH INTERNATIONAL CONFERENCE ON MECHANICAL MATERIALS AND MANUFACTURING ENGINEERING (MMME 2016), 2016, 79 : 95 - 104
  • [6] Human Body Full-body Motion Gesture Image Feature Capture in Mobile Sensor Networks
    Yang, Zhaolin
    Ambati, Loknath Sai
    [J]. MOBILE NETWORKS & APPLICATIONS, 2024,
  • [7] Multisensor-Fusion for 3D Full-Body Human Motion Capture
    Pons-Moll, Gerard
    Baak, Andreas
    Helten, Thomas
    Mueller, Meinard
    Seidel, Hans-Peter
    Rosenhahn, Bodo
    [J]. 2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR), 2010, : 663 - 670
  • [8] The Design and Implementation of All-Dimensional Planar Motion Positioning System Based on Multi-Sensor
    Cai Xiaoqing
    Zhang Liangqi
    Xuan Zeyuan
    Wang Shilin
    HE Chunhua
    [J]. PROCEEDINGS OF THE 28TH CHINESE CONTROL AND DECISION CONFERENCE (2016 CCDC), 2016, : 5343 - 5346
  • [9] Authoring Directed Gaze for Full-Body Motion Capture
    Pejsa, Tomislav
    Rakita, Daniel
    Mutlu, Bilge
    Gleicher, Michael
    [J]. ACM TRANSACTIONS ON GRAPHICS, 2016, 35 (06):
  • [10] Design and Implementation of a Multi-Sensor Monitoring System
    Ye Jihua
    Liu Yan
    Nie Xiaoshi
    [J]. 10TH INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE & EDUCATION (ICCSE 2015), 2015, : 921 - 924