We propose a novel method to characterize 3D surfaces through the computation of a function called (multiscale) area projection transform, measuring the likelihood of points in the 3D space to be center of radial symmetry at selected scales (radii).
The function is derived through a simple geometric framework based on parallel surfaces and can be easily computed on triangulated meshes. It measures locally the area of the surface well approximated by a sphere of radius R centered in the point and can be normalized in order to obtain a scale invariant radial symmetry enhancement transform.
This transform can therefore be used to detect and characterize salient regions like approximately spherical and approximately cylindrical surface parts and, being robust against holes and missing parts, it is suitable for real world applications e.g. anatomical features detection. Furthermore, its histograms can be effectively used to build a global shape descriptor that provides very good results in shape retrieval experiments: it is constantly among the top rated methods for nonrigid shape retrieval in recent contests and the best performing one in human body shape retrieval.
A.Giachetti and C. Lovato, Radial Symmetry Detection and Shape Characterization with the Multiscale Area Projection Transform Computer Graphics Forum 31:5 pp. 1669-1678 (SGP 2012)
A simple program to compute MAPT on .off triangulated geometries is available following this link. Source code is available upon request (andrea.giachetti(at)univr.it)