5th International Conference on Spoken Language Processing
Visual feature extraction method now becomes the key technique in automatic speechreading systems. However it still remains a difficult problem due to large inter-person and intra-person appearance variabilities. In this paper, we extend the normal active shape model to a hierarchy probability-based framework, which can model a complex shape, such as human face. It decomposes the complex shape into two layers: the global shape including the position, scale and rotation of local shapes (such as eyes, nose, mouth and chin); the local simple shape in normal form. The two layers describe the global variation and local variation respectively, and are combined into a probability framework. It can perform fully automatic facial features locating in speechreading, or face recognition.
Bibliographic reference. Xu, Yanjun / Du, Limin / Li, Guoqiang / Hou, Ziqiang (1998): "A hierarchy probability-based visual features extraction method for speechreading", In ICSLP-1998, paper 0187.