Skip to main content
Article thumbnail
Location of Repository

A Statistical Approach to Facial Identification

By L.C. Morecroft

Abstract

This thesis describes the development of statistical methods for facial identification. The objective is to provide a technique which can provide answers based on probabilities to the question of whether two images of a face are from the same person or whether there could be two different people whose facial images match equally well. The aim would be to contribute to evidence that an image captured, for example, at a crime scene by CCTV, is that of a suspect in custody. The methods developed are based on the underlying mathematics of faces (specifically the shape of the configuration of identified landmarks) At present expert witnesses carry out facial comparisons to assess how alike two faces are and their declared expert opinions are inevitably subjective. \ud \ud To develop the method a large population study was carried out to explore facial variation. Sets of measurements of landmarks were digitally taken from ≈3000 facial images and Procrustes analyses were performed to extract the underlying face shapes and used to estimate the parameters in statistical model for the population of face shapes. This allows pairs of faces to be compared in relation to population variability using a multivariate normal likelihood ratio (MVNLR) procedure. The MVNLR technique is a recognised means for evidence evaluation, and is widely used for example on trace evidence and DNA matching. However, many modifications and adaptations were required because of unique aspects of facial data such as high dimensionality, differential reliabilities of landmark identification and differential distinctiveness within the population of certain facial features. \ud \ud The thesis describes techniques of selection of appropriate landmarks and novel dimensionality reduction methods to accommodate these aspects involving non-sequential selection of principal components (to avoid ephemeral facial expressions) and balancing of measures of reliability against selectivity and specificity. \u

Publisher: School of Mathematics and Statistics (Sheffield)
Year: 2009
OAI identifier: oai:etheses.whiterose.ac.uk:574

Suggested articles

Citations

  1. (1994). (ed.) ‘Anthropometry of the head and face’, doi
  2. (2003). A Japanese computer-assisted facial identification system successfully identifies non-Japanese faces’ Forensic Sci. doi
  3. (2001). Active Appearance Models‟, doi
  4. (2000). Computer-assisted facial image identification system using a 3D physiognomic rangefinder’ Forensic Sci. doi
  5. (1997). Construction and assessment of classification rules, doi
  6. (2005). EigenFit – the generation of photographic quality facial composites‟ The Journal of Forensic Science, doi
  7. (1987). Evaluation of the likelihood ratio for fibre transfer evidence in criminal cases’
  8. (2004). Evaluation of trace evidence in the form of multivariate data’ doi
  9. (2000). Evolving faces from principal components‟. doi
  10. (1993). Facial expression of emotion. doi
  11. (2006). Facing the Future: Errors Involved in Biometric Measurement of the Human Face’, Forensic Science: Classroom to Courtroom,
  12. (2004). Forensic Photogrammetry: a personal perspective’ Geomatics World,
  13. (2002). Individual identification of disguised faces by morphometrical matching’ Forensic Sci. doi
  14. (2005). Introduction to Statistics for Forensic Scientists’, doi
  15. (2001). Modern Applied Statistics with S-PLUS, 3 rd Ed doi
  16. (1991). Morphometric Tools for Landmark Data: Geometry and Biology’ doi
  17. (2005). On the measurement and analysis of asymmetry with applications to facial modelling’ doi
  18. (1991). Procrustes methods in the statistical analysis of shape’,
  19. (1984). Shape Manifolds, doi
  20. (2005). shirleymckie.com’ (accessed 20/04/05) URL http://www.shirleymckie.com/
  21. (1986). Size and Shape Spaces for Landmark Data in Two Dimensions’ (with discussion), doi
  22. (1992). Statistical inference in crime investigations using deoxyribonucleic acid profiling’ (with discussion). doi
  23. (2004). Statistics and the Evaluation of Evidence for Forensic Scientists’, doi
  24. (2005). The Daubert Worldview’ (work in progress, last revised 04/03/05, accessed 19/04/05) URL http://www.daubertontheweb.com/
  25. (2004). The Forensic Science Project’ (last updated 06/03/04, accessed 20/04/05)
  26. (1999). Twoand three-dimensional patterns of the face’, doi

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.