A New Manifold Representation for Visual Speech Recognition

In this paper, we propose a new manifold representation for visual speech recognition. The developed system consists of three main steps: a) lip extraction from input video data, b) generate the expectation-maximization PCA (EMPCA) manifolds for the entire image sequence and perform manifold interpolation and re-sampling, c) classify the manifolds using a HMM classifier to identify the words described by the lips motions in the input video sequence.

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