A novel automatic motion capture data recognition method based on statistics learning and subspace

Authors:
Jian Xiang;Hongli Zhu
Affiliations:
School of Information and Electronic Engineering, ZheJiang University of Science and Technology, Hangzhou 310023, China.;College of Information and Electrical Engineering, ZheJiang University City College, Hangzhou 310015, China
Venue:
International Journal of Computer Applications in Technology
Year:
2010

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Abstract

In this paper, we propose a motion recognition method based on motion capture data. To recognise motion type, a generalised Isomap non-linear dimension reduction based on Radius Basis Function (RBF) networks and feature extraction is used to project original motion data into low-dimensional subspace. Then, some motion-type classifiers are learned for each human's joint in subspace. Then, we use ensemble reinforcement learning to enhance learning results. Experimental results show that our methods are effective for 3D human motion recognition and control.