Kernal principal component analysis of the ear morphology

This paper describes features in the ear shape that change across a population of ears and explores the corresponding changes in ear acoustics. The statistical analysis conducted over the space of ear shapes uses a kernel principal component analysis (KPCA). Further, it utilizes the framework of large deformation diffeomorphic metric mapping and the vector space that is constructed over the space of initial momentums, which describes the diffeomorphic transformations from the reference template ear shape. The population of ear shapes examined by the KPCA are 124 left and right ear shapes from the SYMARE database that were rigidly aligned to the template (population average) ear. In the work presented here we show the morphological variations captured by the first two kernel principal components, and also show the acoustic transfer functions of the ears which are computed using fast multipole boundary element method simulations