Analysis of segmented human body scans

Abstract

Analysis on a dataset of 3D scanned surfaces have presented problems because of incompleteness on the surfaces and because of variances in shape, size and pose. In this paper, a high-resolution generic model is aligned to data in the Civilian American and European Surface Anthropometry Resources (CAESAR) database in order to obtain a consistent parameterization. A Radial Basis Function (RBF) network is built for rough deformation by using landmark information from the generic model, anatomical landmarks provided by CAESAR dataset and virtual landmarks created automatically for geometric deformation. Fine mapping then successfully applies a weighted sum of errors on both surface data and the smoothness of deformation. Compared with previous methods, our approach makes robust alignment in a higher efficiency. This consistent parameterization also makes it possible for Principal Components Analysis (PCA) on the whole body as well as human body segments. Our analysis on segmented bodies displays a richer variation than that of the whole body. This analysis indicates that a wider application of human body reconstruction with segments is possible in computer animation.