Exploring the space of human body shapes: data-driven synthesis under anthropometric control

In this paper, we demonstrate a system for synthesizing high-resolution, realistic 3D human body shapes according to user-specified anthropometric parameters. We begin with a corpus of whole-body 3D laser range scans of 250 different people. For each scan, we warp a common template mesh to fit each scanned shape, thereby creating a one-to-one vertex correspondence between each of the example body shapes. Once we have a common surface representation for each example, we then use principal component analysis to reduce the data storage requirements. The final step is to relate the variation of body shape with concrete parameters, such as body circumferences, point-to-point measurements, etc. These parameters can then be used as "sliders" to synthesize new individuals with the required attributes, or to edit the attributes of scanned individuals.