Model Based Coding : Initialization, Parameter Extraction and Evaluation

This thesis covers topics relevant to model-based coding. Model-based coding is a promising very low bit rate video coding technique. The idea behind this technique is to parameterize a talking head and to extract and transmit the parameters describing facial movements. At the receiver, the parameters are used to reconstruct the talking head. Since only high-level animation parameters are transmitted, very high compression can be achieved with this coding scheme. This thesis covers the following three key problems. Although it is a fundamental problem, the initialization problem, has been neglected some extent in the literature. In this thesis, we pay particular attention to the study of this problem. We propose a pseudo-automatic initialization scheme: an Analysis-by-Synthesis scheme based on Simulated Annealing. It has been proved to be an efficient scheme. Owing to technical advance today and the newly emerged MPEG-4 standard, new schemes of performing texture mapping and motion estimation are suggested which use sample based direct texture mapping; the feasibility of using active motion estimation is explored which proves to be able to give more than 10 times tracking resolution. Based on the matured face detection technique, Dynamic Programming is introduced to face detection module and work for face tracking. Another important problem addressed in this thesis is how to evaluate the face tracking techniques. We studied the evaluation problems by examining the commonly used method, which employs a physical magnetic sensor to provide "ground truth". In this thesis we point out that it is quite misleading to use such a method