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- W2022036083 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." @default.
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- W2022036083 date "2010-01-01" @default.
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- W2022036083 title "A novel automatic motion capture data recognition method based on statistics learning and subspace" @default.
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- W2022036083 doi "https://doi.org/10.1504/ijcat.2010.034138" @default.
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