A novel automatic motion capture data recognition method based on statistics learning and subspace Online publication date: Fri, 16-Jul-2010
by Jian Xiang, Hongli Zhu
International Journal of Computer Applications in Technology (IJCAT), Vol. 38, No. 1/2/3, 2010
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.
Online publication date: Fri, 16-Jul-2010
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