  Ears are a particularly difficult region of the human face to model, not only
due to the non-rigid deformations existing between shapes but also to the
challenges in processing the retrieved data. The first step towards obtaining a
good model is to have complete scans in correspondence, but these usually
present a higher amount of occlusions, noise and outliers when compared to most
face regions, thus requiring a specific procedure. Therefore, we propose a
complete pipeline taking as input unordered 3D point clouds with the
aforementioned problems, and producing as output a dataset in correspondence,
with completion of the missing data. We provide a comparison of several
state-of-the-art registration methods and propose a new approach for one of the
steps of the pipeline, with better performance for our data.
