Marker-less motion capture system using OpenPose

被引：3
|
作者：
Feng, B. [1 ]
Powell, D. W. [2 ]
Doblas, A. [1 ]
机构：
[1] Univ Memphis, Dept Elect & Comp Engn, Memphis, TN 38152 USA
[2] Univ Memphis, Coll Heath Sci, Memphis, TN 38152 USA
来源：
PATTERN RECOGNITION AND TRACKING XXXIII | 2022年 / 12101卷
关键词：
motion capture system; markerless; body biometrics;
D O I：
10.1117/12.2619059
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Motion capture systems are widely used to measure athletic performance and as a diagnostic tool in sports medicine. Standard motion capture systems record body movement using: (1) a set of cameras to localize body segments; or (2) specialized suits in which inertial measurement units are directly attached to body segments. The major drawbacks of these systems are limited portability, affordability, and accessibility. This contribution presents a markerless motion capture system using a commercially available sports camera and the OpenPose human pose estimation algorithm. We have validated the proposed markerless system by analyzing the human biometrics during running and jumping movements.
引用
收藏
页数：10
相关论文
共 50 条
  • [1] Reproduction of a human motion based on marker-less motion capture
    Yonemoto, Satoshi
    Arita, Daisaku
    Taniguchi, Rin-Ichiro
    Research Reports on Information Science and Electrical Engineering of Kyushu University, 2000, 5 (01): : 75 - 80
  • [2] Real-time drowsiness evaluation system using marker-less facial motion capture
    Koshi, Yudai
    Tanaka, Hisaya
    ARTIFICIAL LIFE AND ROBOTICS, 2024, 29 (04) : 573 - 578
  • [3] Reliability Of Vertical Oscillation During Running Using Marker-less Motion Capture
    Rogler, Isabella C.
    Moran, Matthew F.
    Wager, Justin C.
    MEDICINE & SCIENCE IN SPORTS & EXERCISE, 2024, 56 (10) : 987 - 987
  • [4] A system for marker-less human motion estimation
    Rosenhahn, B
    Kersting, UG
    Smith, AW
    Gurney, JK
    Brox, T
    Klette, R
    PATTERN RECOGNITION, PROCEEDINGS, 2005, 3663 : 230 - 237
  • [5] Marker-less facial motion capture based on the recognition of the parts
    Akagi, Yasuhiro
    Furukawa, Ryo
    Sagawa, Ryusuke
    Ogawara, Koichi
    Kawasaki, Hiroshi
    Seimitsu Kogaku Kaishi/Journal of the Japan Society for Precision Engineering, 2013, 79 (11): : 1152 - 1158
  • [6] Human gait assessment using a 3D marker-less multimodal motion capture system
    Rodrigues, Thiago Braga
    Salgado, Debora Pereira
    Cathain, Ciaran O.
    O'Connor, Noel
    Murray, Niall
    MULTIMEDIA TOOLS AND APPLICATIONS, 2020, 79 (3-4) : 2629 - 2651
  • [7] Human gait assessment using a 3D marker-less multimodal motion capture system
    Thiago Braga Rodrigues
    Debora Pereira Salgado
    Ciarán Ó Catháin
    Noel O’Connor
    Niall Murray
    Multimedia Tools and Applications, 2020, 79 : 2629 - 2651
  • [8] Influence Of Sex On Marker To Marker-less Motion Capture Evaluations Of Gait Biomechanics
    Wills, Neil A.
    Pamukoff, Derek N.
    Eghobamien, Iwi J.
    Nwaokoro, Vital I.
    MEDICINE & SCIENCE IN SPORTS & EXERCISE, 2024, 56 (10) : 989 - 990
  • [9] EgoCap: Egocentric Marker-less Motion Capture with Two Fisheye Cameras
    Rhodin, Helge
    Shafiei, Mohammad
    Richardt, Christian
    Seidel, Hans-Peter
    Casas, Dan
    Schiele, Bernt
    Insafutdinov, Eldar
    Theobalt, Christian
    ACM TRANSACTIONS ON GRAPHICS, 2016, 35 (06):
  • [10] Comparison of marker-less and marker-based motion capture for baseball pitching kinematics
    Fleisig, Glenn S.
    Slowik, Jonathan S.
    Wassom, Derek
    Yanagita, Yuki
    Bishop, Jasper
    Diffendaffer, Alek
    SPORTS BIOMECHANICS, 2024, 23 (12) : 2950 - 2959
12345