Dimension Reduction in 3D Gesture Recognition Using Meshless Parameterization

3D gesture recognition offers more details data but leads to computational hurdles which do not support real-time gesture recognition application. In this paper, we introduce a method of dimension reduction for 3D gesture recognition. Our method uses meshless parameterization to perform dimension reduction in modeling process and extracts gesture data, in order to reduce the computation complexity. In addition, this method also maintains the 3D gesture information and result novel features vectors for 3D gesture recognition. The computational efficiency of dimension reduction and by using novel features vectors makes 3D gesture recognition more possible to achieve real-time performance.

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