Pictorial statistics-visualization of high-dimensional statistical distributions

A general framework for visualization of statistical properties of high-dimensional pattern samples and the related computational steps are introduced. These procedures are exemplified on applications in anthropometrical research (shape information in faces) but can be easily generalized to various other morphometrical questions and data sets with pattern structure, e.g., data stemming from sensor arrays. Presently, the visualization techniques illustrated concentrate on (higher) moments of first order. It is suggested, how moments of second order can be visualized by animations and how this approach can be used in the context of comparative visualization.