Oral features localization based on HASM

The principal idea of this research for visual speech synthesis realism is that oral features localization provides the precise geometrical information for oral images of speech sound. In this research, Hierarchical Active Shape Model (HASM) is used as local texture model. In the structuring local texture model, the local texture model is the main clue. The optimal oral features localizations are decided by Mahalanobis distance. This research utilizes variable step strategy, variable angle strategy and oral images clustering strategy to greatly improve the accuracy and efficiency of inter lip localization and special lip shape. The result shows that the accuracy and efficiency are up to 90%.