Frame adaptive segmentation for model-based videophone coding

Very high compression in videophone coding can be reached successfully only if model-based segmentation is performed to allow suitable bit allocation. The exploitation of a priori knowledge suggests the application of fast and simple segmentation algorithms oriented at partitioning the image into variable resolution domains for subsequent texture encoding. In this paper we describe, together with the achieved preliminary results, a model-based approach to image segmentation relying on the estimation of the face symmetry axis and of the primary facial features. Through these parameters a flexible lattice is adapted frame by frame on the image, identifying a time-varying net of triangular patches whose texture is eventually encoded via Legendre basis functions. Target applications for videophone coding of QCIF color sequences at very low bitrate, less than 16 Kbit/sec., are foreseen