Human face analysis based on distributed two-dimensional appearance models

This paper proposes a method for building a system which automatically images the components of a human face. The method is useful in any number of different perspectives. It is assumed that facial appearance depends on the camera angle and perspective as well as individual facial characteristics. Appearances of a face are classified based on the applicable possibilities of the vision algorithms. Two-dimensional models of different facial appearances are constructed and the algorithms based on these models are applied in parallel to each scene in a top-down mode. An appearance model consists of agents, each of which has simple functions. The results of the analysis are re-combined with their assumptions based on the Dempster-Shafer probability model. Experiments using actual facial images confirm the usefulness of the proposed method.

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