Facial feature estimation from the local structural diversity of skulls

In forensics, the craniofacial reconstruction is employed as an initialization of the identification from skulls. It is a challenging work to develop such a system due to the ambiguity in the relationship between the shape of the skull and the face. In this paper, we present a facial feature estimation method based on the local structural diversity of skulls. A mapping system between the skull structural measurements and the facial feature shapes is established via a RBF regression model. The PCA subspaces are established for the local facial features and the skull structures. Moreover, we investigate the attribute vector of the facial feature polyhedron and the distance graph of the skull structure as the shape descriptors. The experiments demonstrate the feature outlooks can be estimated feasibly and efficiently.