title: Craniofacial reconstruction evaluation by geodesic network.
abstract: Craniofacial reconstruction is to estimate an individual's face model from its skull. It has a widespread application in forensic medicine, archeology, medical cosmetic surgery, and so forth. However, little attention is paid to the evaluation of craniofacial reconstruction. This paper proposes an objective method to evaluate globally and locally the reconstructed craniofacial faces based on the geodesic network. Firstly, the geodesic networks of the reconstructed craniofacial face and the original face are built, respectively, by geodesics and isogeodesics, whose intersections are network vertices. Then, the absolute value of the correlation coefficient of the features of all corresponding geodesic network vertices between two models is taken as the holistic similarity, where the weighted average of the shape index values in a neighborhood is defined as the feature of each network vertex. Moreover, the geodesic network vertices of each model are divided into six subareas, that is, forehead, eyes, nose, mouth, cheeks, and chin, and the local similarity is measured for each subarea. Experiments using 100 pairs of reconstructed craniofacial faces and their corresponding original faces show that the evaluation by our method is roughly consistent with the subjective evaluation derived from thirty-five persons in five groups.
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China ; College of Software and Technology, Qingdao University, Qingdao 266071, China.
authors.forename: Junli
authors.initials: J
authors.lastname: Zhao
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China.
authors.forename: Cuiting
authors.initials: C
authors.lastname: Liu
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China.
authors.forename: Zhongke
authors.initials: Z
authors.lastname: Wu
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China.
authors.forename: Fuqing
authors.initials: F
authors.lastname: Duan
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China.
authors.forename: Kang
authors.initials: K
authors.lastname: Wang
authors.affiliation: Engineering Research Center of Virtual Reality and Applications, Ministry of Education, Beijing Key Laboratory of Digital Preservation and Virtual Reality for Cultural Heritage, Beijing Normal University, Beijing 100875, China.
authors.forename: Taorui
authors.initials: T
authors.lastname: Jia
authors.affiliation: Université de Bretagne-Sud, CNRS UMR 6205, LMBA, Campus de Tohannic, BP 573, 56000 Vannes, France.
authors.forename: Quansheng
authors.initials: Q
authors.lastname: Liu
mesh_terms: D000328:Adult; D000368:Aged; D005145:Face / Q000033:anatomy & histology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008875:Middle Aged; D012886:Skull / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D014057:Tomography, X-Ray Computed / Q000379:methods*; D055815:Young Adult