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|Title:||Displacement estimation in micro-sensor motion capture|
|Keywords:||Complementary Kalman filter|
Human motion capture
|Source:||Meng, X.,Sun, S.,Ji, L.,Wu, J.,Wong, W.-C. (2010). Displacement estimation in micro-sensor motion capture. Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics : 2611-2618. ScholarBank@NUS Repository. https://doi.org/10.1109/ICSMC.2010.5641907|
|Abstract:||The use of wearable micro-sensors provides an easy-to-use and cost-efficient way for human motion capture. It is essential but difficult to estimate the global displacements of human walking in micro-sensor motion capture system. This paper proposes a novel method to estimate the global displacements of walking based on the pedestrian dead reckoning technique. The global displacements are obtained from the estimated walking distance and the heading direction. Walking distance is calculated using the extension and flexion angles of the lower limbs. Heading is estimated by the fusion of magnetometer and gyroscope readings accomplished by a complementary Kalman filter. The displacements are used to drive a skeleton model to animate the walking movements of the subject. Walking experiments have demonstrated that the proposed method can estimate the displacements accurately and animate the human walking motions smoothly and vividly. ©2010 IEEE.|
|Source Title:||Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics|
|Appears in Collections:||Staff Publications|
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