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Ambulatory real-time micro-sensor motion capture

Published: 16 April 2012 Publication History

Abstract

Commercial optical human motion capture systems perform well in studio-like environments, but they do not provide solution in daily-life surroundings. Micro-sensor motion capture has shown its potentials because of its ubiquity and low cost. We present an ambulatory low-cost real-time motion capture system using wearable micro-sensors (accelerometers, magnetometers and gyroscopes), which can capture and reconstruct human motion in real-time almost everywhere. It mainly consists of three parts: a sensor subsystem, a data fusion subsystem and an animation subsystem. The sensor subsystem collects human motion signals and transfers them into the data fusion subsystem. The data fusion subsystem performs sensor fusion to obtain motion information, i.e., the orientation and position of each body segment. Using the motion information from the data fusion subsystem, the animation subsystem drives the avatar in the 3D virtual world in order to reconstruct human motion. All the processes are accomplished in real-time. The experimental results show that our system can capture motions and drive animations in real-time vividly without drift and delay. And the output from our system can be made use of in film-making, sports training and argument reality applications, etc.

References

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Vicon. http://www.vicon.com.
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S. Y. Sun, X. L. Meng, L. Y. Ji, J. K. Wu and W. C. Wong. Adaptive Sensor Data Fusion in Motion Capture. Fusion, 26-29 July 2010. EICC, Edinburgh, UK.
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X. L. Meng, S. Y. Sun, L. Y. Ji, J. K. Wu and W. C. Wong. Estimation of Center of Mass Displacement based on Gait Analysis. BSN, 23-25 May 2011. Dallas, US.
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G. H. Tao, S. Y. Sun, S. Huang, Z. P. Huang and J. K. Wu. Human modeling and real-time motion reconstruction for micro-sensor motion capture. VECIMS, 19-21 Sept. 2011. Ottawa, Canada.
[5]
http://snarc.ia.ac.cn.

Cited By

View all
  • (2014)Wearable Sensor Integration and Bio-motion Capture: A Practical PerspectiveBody Sensor Networks10.1007/978-1-4471-6374-9_12(495-526)Online publication date: 12-Mar-2014
  • (2013)Tracer: Taming Anomalous Events with CRFID Tags for Trajectory ManagementInternational Journal of Distributed Sensor Networks10.1155/2013/1483539:11(148353)Online publication date: Jan-2013

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Published In

cover image ACM Conferences
IPSN '12: Proceedings of the 11th international conference on Information Processing in Sensor Networks
April 2012
354 pages
ISBN:9781450312271
DOI:10.1145/2185677

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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Author Tags

  1. data fusion
  2. human motion capture
  3. micro-sensor
  4. motion reconstruction
  5. real-time animation

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Overall Acceptance Rate 143 of 593 submissions, 24%

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Cited By

View all
  • (2014)Wearable Sensor Integration and Bio-motion Capture: A Practical PerspectiveBody Sensor Networks10.1007/978-1-4471-6374-9_12(495-526)Online publication date: 12-Mar-2014
  • (2013)Tracer: Taming Anomalous Events with CRFID Tags for Trajectory ManagementInternational Journal of Distributed Sensor Networks10.1155/2013/1483539:11(148353)Online publication date: Jan-2013

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