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Most current approaches in action recognition face difficulties that cannot handle recognition of multiple actions, fusion of multiple features, and recognition of action in frame by frame model, incremental learning of new action samples and application of position information of space-time interest points to improve performance simultaneously. In this paper, we propose a novel approach based on...
In this paper we propose a view invariant hand gesture recognition algorithm based on the assumption that the gesture trajectory is almost in a plane, which we call principal gesture plane. We use Least Squares Method to estimate the plane and project the 3D trajectory onto it. The viewpoint-dependent problem is solved by the projection. HMMs are chosen to model the gestures. We have evaluated the...
This study presents an approach to Hidden Markov Models (HMM)-based spontaneous speech synthesis with pronunciation variation for better spontaneity. Pronunciation variation generally occurs in spontaneous speech and plays an important role in expressing the spontaneity. In this study, a state-based transformation function is adopted to model the relation between read speech and the corresponding...
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