Geometrical processing of 3D body scanner data for anthropometric applications

In this paper we describe a pipeline for the geometric processing of 3D meshes obtained by whole body scanners, aimed at providing support for anthropometric measurements. The output of whole body scanners is a cloud of points, usually transformed in a triangulated mesh through the use of specific algorithms in order to support the 3D visualization of the surface and the extraction of meaningful anthropometric landmarks and measurements. Anthropometric analysis is usually performed by using device specific and closed software solutions provided by scanner manufacturers, and requires often a careful acquisition, with strong constraints on subject pose. This may create problems in comparing data acquired in different places and performing large-scale multi-centric studies as well as in applying advanced shape analysis tools on the captured models. The aim of our work is to overcome these problems by selecting and customizing geometrical processing tools able to create an open and device-independent pipeline for the analysis of body scanner data. We also aim at developing and validating methods to extract automatically feature points, body segments and relevant measurements that can be used in anthropometric and metabolic research. The paper presents a general description of the proposed processing pipeline and the currently developed modules (hole filling, skeleton-based segmentation, heat kernel based landmark location), showing their usefulness in the automatic and computer assisted evaluation of anthropometric data.