Analysis and Synthesis of Facial Expressions - 3D Modeling and Animation: Synthesis and Analysis Techniques for the Human Body - page 247

Figure 1. Analysis-synthesis loop of the model-based estimator.

The hierarchical estimation can be embedded into an analysis-synthesis loop as
shown in Figure 1. In the analysis part, the algorithm estimates the parameter
changes between the previous synthetic frame Î and the current frame I from

the video sequence. The synthetic frame Î is obtained by rendering the 3-D model
(synthesis part) with the previously determined parameters. This approximative
solution is used to compensate the differences between the two frames by
rendering the deformed 3-D model at the new position. The synthetic frame now
approximates the camera frame much better. The remaining linearization errors
are reduced by iterating through different levels of resolution. By estimating the
parameter changes with a synthetic frame that corresponds to the 3-D model, an
error accumulation over time is avoided.

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Linear Illumination Analysis

For natural video capture conditions, scene lighting often varies over time. This
illumination variability has a considerable influence not only on the visual
appearance of the objects in the scene, but also on the performance of computer
vision algorithms or video-coding methods. The efficiency and robustness of
these algorithms can be significantly improved by removing the undesired effects
of changing illumination. In this section, we introduce a 3-D model-based
technique for estimating and manipulating the lighting in an image sequence
(Eisert et al., 2002). The current scene lighting is estimated for each frame
exploiting 3-D model information and by synthetic re-lighting of the original video
frames. To provide the estimator with surface-normal information, the objects in