A New Manifold Representation for Visual Speech Recognition
Dahai Yu, Ovidiu Ghita, Alistair Sutherland, Paul F. Whelan · 2007
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.