Statistical shape analysis is a geometrical analysis from a set of
shapes in which statistics are measured to describe geometrical
properties from similar shapes or different groups, for instance, the
difference between male and female Gorilla skull shapes, normal and
pathological bone shapes, etc. Some of the important aspects of shape
analysis are to obtain a measure of distance between shapes, to estimate
average shapes from a (possibly random) sample and to estimate shape
variability in a sample[1]. One of the main methods used is principal
component analysis. Specific applications of shape analysis may be found
in archaeology, architecture, biology, geography, geology, agriculture,
genetics, medical imaging, security applications such as face
recognition, entertainment industry (movies, games), computer-aided
design and manufacturing. This is a proposal for a new Brief on
statistical shape analysis and the various new parametric and
non-parametric methods utilized to facilitate shape analysis.