Shui, W., Zhou, M., Maddock, S. orcid.org/0000-0003-3179-0263 et al. (6 more authors) (2020) A computerized craniofacial reconstruction method for an unidentified skull based on statistical shape models. Multimedia Tools and Applications, 79. pp. 25589-25611. ISSN 1380-7501
Abstract
Craniofacial reconstruction (CFR) has been widely used to produce the facial appearance of an unidentified skull in the realm of forensic science. Many studies have indicated that the computerized CFR approach is fast, flexible, consistent and objective in comparison to the traditional manual CFR approach. This paper presents a computerized CFR system called CFRTools, which features a CFR method based on a statistical shape model (SSM) of living human head models. Given an unidentified skull, a geometrically-similar template skull is chosen as a template, and a non-registration method is used to improve the accuracy of the construction of dense corresponding vertices through the alignment of the template and the unidentified skull. Generalized Procrustes analysis (GPA) and principal component analysis (PCA) are carried out to construct the skull and face SSMs. The sex of the unidentified skull is then predicted based on skull SSM and centroid size, rather than geometric measurements based on anatomical landmarks. Furthermore, a craniofacial morphological relationship which is learnt from the principal component (PC) scores of the skull and face dataset is used to produce a possible reconstructed face. Finally, multiple possible reconstructed faces for the same skull can further be recreated based on adjusting the PC coefficients. The experimental results show that the average rate of sex classification is 97.14% and the reconstructed face of the unidentified skull can be produced. In addition, experts’ understanding and experience can be harnessed in production of face variations for the same skull, which can further be used as a reference for portraiture creation.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © Springer Science+Business Media, LLC, part of Springer Nature 2020. This is an author-produced version of a paper subsequently published in Multimedia Tools and Applications. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Computerized craniofacial reconstruction; Skull digitization; Skull registration; Sex classification; Facial shape editing |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 06 Jul 2020 10:20 |
Last Modified: | 21 Oct 2021 18:00 |
Status: | Published |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1007/s11042-020-09189-7 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:162907 |