Geometric and Statistical Methods for Processing 3D Anthropometric Data

3D anthropometric data obtained from 3D imaging technology provide unprecedented information about the human shape. At the same time, 3D data present tremendous new challenges. New software tools and analytical methods have to be designed to realize the full potential of the 3D data. One prominent character of the 3D data is that they are a collection of coordinates in 3-space and do not have a natural order. This poses problems for performing statistical analysis. In order to make sense about this new type of data, 3D points have to be registered such that meaningful correspondences across all the models can be established. Other issues include data completion, compression, and visualization. In this paper, we describe a framework and the techniques involved in processing the 3D anthropometric data for the purpose of making them usable for designing products that fit the human shapes.