BibTeX entry

@PHDTHESIS{200511Ioannis_Douros,
  AUTHOR={Ioannis Douros},
  TITLE={Calculating the Curvature Shape Characteristics of the
    Human Body from 3D Scanner Data},
  SCHOOL={University of London},
  MONTH=Nov,
  YEAR=2005,
  URL={http://www.bmva.org/theses/2005/2005-douros.pdf},
}

Abstract

In recent years, there have been significant advances in the development and manufacturing of 3D scanners capable of capturing detailed (external) images of whole human bodies. Such hardware offers the opportunity to collect information that could be used to describe, interpret and analyse the shape of the human body for a variety of applications where shape information plays a vital role (e.g. apparel sizing and customisation; medical research in fields such as nutrition, obesity/anorexia and perceptive psychology; ergonomics for vehicle and furniture design). However, the representations delivered by such hardware typically consist of unstructured or partially structured point clouds, whereas it would be desirable to have models that allow shape-related information to be more immediately accessible. This thesis describes a method of extracting the differential geometry properties of the body surface from unorganized point cloud datasets. In effect, this is a way of constructing curvature maps that allows the detection on the surface of features that are deformable (such as ridges) rather than reformable under certain transformations. Such features could subsequently be used to interpret the topology of a human body and to enable classification according to its shape, rather than its size (as is currently the standard practice for many of the applications concerned).