Figure 1: A,B: volume rendering of the area projection transform computed at two different scales on an ant model is high near centers of radial symmetry at the selected scales. The joint multiscale map computed on a wide radius range can simultaneously detect centers of symmetry at variable scales (C). The behavior of these maps is qualitatively unchanged removing randomly 50% of the faces (D) or, thanks to adaptive smoothing (see text), adding relevant noise to vertex positions (E). Abstract

In this paper, we present an automatic tool for estimating geometrical parameters from 3-D human scans independent on pose and robustly against the topological noise. It is based on an automatic segmentation of body parts exploiting curve skeleton processing and ad hoc heuristics able to remove problems due to different acquisition poses and body types. The software is able to locate body trunk and limbs, detect their directions, and compute parameters like volumes, areas, girths, and lengths. Experimental results demonstrate that measurements provided by our system on 3-D body scans of normal and overweight subjects acquired in different poses are highly correlated with the body fat estimates obtained on the same subjects with dual-energy X-rays absorptiometry (DXA) scanning. In particular, maximal lengths and girths, not requiring precise localization of anatomical landmarks, demonstrate a good correlation (up to 96%) with the body fat and trunk fat. Regression models based on our automatic measurements can be used to predict body fat values reasonably well.

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