Logo
Logo

Goldsmiths - University of London

Exact solutions to Bayesian and maximum likelihood problems in facial identification when population and error distributions are known

Allen, Rory. 2008. Exact solutions to Bayesian and maximum likelihood problems in facial identification when population and error distributions are known. Forensic Science International(179), pp. 211-218. [Article]

[img]
Preview
Text (Published in Forensic Science International 179 (2008) 211–218)
FacesArticle.pdf - Published Version

Download (176kB) | Preview

Abstract or Description

The reliability of traditional photogrammetric identification techniques using a small number of facial landmarks has recently come in for
criticism. However, the transformation of parameters into a new face space in which the error distributions are orthogonal, yields a maximum
likelihood solution to the problem of identifying a photographed face from a small, known, population which, in a simulated example, raises the
success rate from 20% to 93%. A full transformation yielding simultaneously independent population and error distributions can be derived from
raw population and error data using a straightforward computer procedure. Such a transformation facilitates computations for the situation where a
single suspect is held in custody and the likelihood ratio of his being identical with a photograph is desired. It seems premature to condemn
photogrammetry until the more efficient data-analysis approach outlined in this paper has been applied and tested.

Item Type: Article

Departments, Centres and Research Units:

Psychology

Dates:

DateEvent
17 July 2008Published

Item ID:

4672

Date Deposited:

23 Nov 2010 13:38

Last Modified:

30 Jun 2017 12:51

URI: http://research.gold.ac.uk/id/eprint/4672

View statistics for this item...

Edit Record Edit Record (login required)