Centre for Anatomy and Human Identification staff developed, evaluated and applied techniques, standards and datasets for facial depiction and identification of the dead.
This included creating an international forensic tool that has enhanced forensic identification from human remains. Use of this tool has improved law enforcement services and disaster victim identification.
The work also delivered both highly skilled people and international standards in forensic craniofacial identification.
Finally, the craniofacial depiction of historical figures and ancient human remains using the tool enlarged and enhanced public engagement with science and art internationally.
The team have employed the craniofacial computer system to analyse, authenticate and/or depict the faces of key historical figures, such as Richard III, Mary Queen of Scots, Robert Burns, J.S Bach, Rameses II, Arsinoe - the sister of Cleopatra and St Nicolas.
The research was carried out under the leadership of Professor Caroline Wilkinson and was a collaboration between CAHID and the University of Dundee’s Duncan of Jordanstone College of Art and Design. Professor Wilkinson has subsequently left CAHID.
The researchers involved in the team are Dr Chris Rynn, Caroline Erolin, Janice Aitken and Dr Won-Joon Lee.
Professor Wilkinson created updated and further developed a 3D computerised craniofacial depiction system using existing 3D modelling software and haptic technology, a database of modelled anatomical structures and a 3D facial feature database collected from laser scans. In addition, her team created standards from clinical images and direct measurement of living subjects.
The system was tested in a number of blind studies using CT and laser scan data from living subjects from the USA, Korea and the UK. It was evaluated in relation to the cross-race effect, reliability reproducibility and accuracy. The degree of similarity between the subjects’ face shape and the surface of the craniofacial depiction could be quantified using morphometric and face recognition software.