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The Craniofacial Reconstruction from the Local Structural Diversity of Skulls
Author(s) -
Pei Yuru,
Zha Hongbin,
Yuan Zhongbiao
Publication year - 2008
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2008.01315.x
Subject(s) - artificial intelligence , computer science , image warping , skull , computer vision , feature (linguistics) , craniofacial , pattern recognition (psychology) , feature extraction , initialization , face (sociological concept) , anatomy , biology , social science , linguistics , philosophy , genetics , sociology , programming language
The craniofacial reconstruction is employed as an initialization of the identification from skulls in forensics. In this paper, we present a two‐level craniofacial reconstruction framework based on the local structural diversity of the skulls. On the low level, the holistic reconstruction is formulated as the superimposition of the selected tissue map on the novel skull. The crux is the accurate map registration, which is implemented as a warping guided by the 2D feature curve patterns. The curve pattern extraction under an energy minimization framework is proposed for the automatic feature labeling on the skull depth map. The feature configuration on the warped tissue map is expected to resemble that on the novel skull. In order to make the reconstructed faces personalized, on the high level, the local facial features are estimated from the skull measurements via a RBF model. The RBF model is learnt from a dataset of the skull and the face feature pairs extracted from the head volume data. The experiments demonstrate the facial outlooks can be reconstructed feasibly and efficiently.