Design and implementation of the MARG human body motion tracking system

Real-time tracking of human body motion has applications in tele-operation, synthetic reality and others. A motion tracking system based on use of the MARG sensors has been under development at Naval Postgraduate School and Miami University. The magnetic, angular rate, and gravity (MARG) sensor modules use a combination of three orthogonal magnetometers, three orthogonal angular rate sensors, and three orthogonal accelerometers to measure 3-D orientation of individual limb segments in order to determine posture. This paper presents the latest results of the MARG human body motion tracking system. The design and implementation of a control interface unit (CIU), a real-time 3-D human avatar called "Andy", and a concurrent client-server program are discussed. Experimental testing and evaluation of the overall MARG system is also presented. The system is able to track multiple human limbs in real time. The captured human motion data can be visualized over the Internet by multiple clients using the 3-D avatar.

[1]  Shinichi Shiwa,et al.  Motion tracking method for the CAVE/sup TM/ system , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[2]  Qiang He,et al.  Development and analysis of a real-time human motion tracking system , 2002, Sixth IEEE Workshop on Applications of Computer Vision, 2002. (WACV 2002). Proceedings..

[3]  Tomomasa Sato,et al.  Human motion tracking system based on skeleton and surface integration model using pressure sensors distribution bed , 2000, Proceedings Workshop on Human Motion.

[4]  Jake K. Aggarwal,et al.  Tracking Human Motion in Structured Environments Using a Distributed-Camera System , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[5]  Michael Zyda,et al.  Design and implementation of MARG sensors for 3-DOF orientation measurement of rigid bodies , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[6]  Yoshihiko Nakamura,et al.  Making feasible walking motion of humanoid robots from human motion capture data , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[7]  Frank Biocca,et al.  A Survey of Position Trackers , 1992, Presence: Teleoperators & Virtual Environments.

[8]  Jihong Lee,et al.  Sensor fusion and calibration for motion captures using accelerometers , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[9]  Kosuke Sato,et al.  Human motion capture by integrating gyroscopes and accelerometers , 1996, 1996 IEEE/SICE/RSJ International Conference on Multisensor Fusion and Integration for Intelligent Systems (Cat. No.96TH8242).

[10]  Michael Macedonia,et al.  Games soldiers play , 2002 .

[11]  Alberto Del Bimbo,et al.  Real-time tracking and reproduction of 3D human body motion , 2001, Proceedings 11th International Conference on Image Analysis and Processing.

[12]  Dariu Gavrila,et al.  The Visual Analysis of Human Movement: A Survey , 1999, Comput. Vis. Image Underst..

[13]  Christopher G. Atkeson,et al.  Adapting human motion for the control of a humanoid robot , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[14]  Ioannis A. Kakadiaris,et al.  Model-Based Estimation of 3D Human Motion , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[15]  Robert B. McGhee,et al.  An improved quaternion-based Kalman filter for real-time tracking of rigid body orientation , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).