Statistics Seminar: "An Investigation into the Human Face: Statistical Models for Manifold Data"

Abstract: Three-dimensional surface imaging, through laser-scanning or stereo-photogrammetry, provides high-resolution data defining the surface shape of objects. Using a human face as this object, each image corresponds to an observation, a manifold, represented by a triangulated point cloud. In an anatomical setting this can provide invaluable quantitative information. Particular applications vary widely including success or failure of cosmetic/reconstructive plastic surgery, facial recognition, facial asymmetry, concepts of sexual dimorphism, and even the survival of mussels (food we consume) given climate change. However, the initial challenge is to characterize these complex surfaces, without laborious manual intervention. Surface curvature provides the key information in doing this, allowing for a creating of a surface “mask” replicable throughout all these objects. Once the full surface representation has been obtained, the new issue arises of how to best characterize and visualize the differences in shape. The issues involved with analysis of this data and multiple visualization methods will be discussed and illustrated.

Host: Todd Kuffner