No abstract

We introduce a formula to compute an optimum 2-D shape-adaptive Karhunen-Loeve transform (KLT) suitable for coding pels in arbitrarily-shaped image segments. The efficiency of the KLT on a 2-D AR(1) process is used to benchmark two other shape-adaptive transforms described in literature. It is shown that the optimum KLT significantly outperforms the well known shape-adaptive DCT method introduced by Gilge et al. (1989) for coding Segments of arbitrary shape in intraframe coding mode. A statistical transform gain close to the Gilge-method can be achieved with a shape-adaptive DCT algorithm introduced by Sikora and Makai (see Proc. Workshop Image Anal. Image Coding, Berlin, FRG, Nov. 1993) which is implemented with much lower complexity

No abstract

We assume that the textures in a video scene can be classified into two categories: textures with unimportant subjective details and the remainder. We utilize this assumption for improved video coding using a texture analyzer and a texture synthesizer. The texture analyzer identifies the texture regions with unimportant subjective details and generates coarse masks as well as side information for the texture synthesizer at the decoder side. The texture synthesizer replaces the identified textures by inserting synthetic textures for the identified regions. The texture analyzer is based on MPEG-7 descriptors. Our approach has been integrated into an H.264/AVC codec. Bit-rate savings up to 19.4% are shown for a semiautomatic texture analyzer given similar subjective quality as the H.264/AVC codec without the presented approach.

We present two recursive methods for the real-time estimation of long-term three-dimensional (3-D) motion parameters from monocular image sequences suitable for synthetic/natural hybrid coding face animation and model-based coding applications. Based on feature point extractions in energy frame, the 3-D motion parameters of a human face are estimated with a predictive approach. The first method uses a recursive linear least squares approach and the second employs a nonlinear extended Kalman filter, which does not rely on a linearized model of the face motion. Both methods perform a prediction and correction loop at every time step. Compared to other methods described in the literature, the recursive and predictive structure of the proposed estimation process solves the