Nose shape estimation and tracking for model-based coding

Feature extraction on the face plays an important role in applications of model based coding and human face recognition. Traditionally, eyes and mouth are considered to be the most significant features contributing to different facial expressions. However, detecting and tracking the nose shape is non-trivial, and plays an equally important role as eyes and mouth for model based coding, especially for analysis and synthesis of realistic facial expressions. In this paper, a feature detection method on the facial organ areas is presented. Individual templates are designed for the nostril and nose-side. First, the feature regions are limited to certain areas by using two-stage region growing methods. Second, the pre-defined templates are applied to extract the shape of the nostril and nose-side. Finally, the extracted feature shapes are exploited to guide a facial model to complete an accurate adaptation. The advantage of the proposed scheme is demonstrated by experiments on real video sequences for low bit rate video coding.