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Computer assisted photo-anthropometric analyses of full-face and profile facial images

Computer assisted photo-anthropometric analyses of full-face and profile facial images

Davis, Josh P. ORCID: 0000-0003-0017-7159, Valentine, Tim and Davis, Robert E. (2010) Computer assisted photo-anthropometric analyses of full-face and profile facial images. Forensic Science International, 200 (1-3). pp. 165-176. ISSN 0379-0738 (doi:10.1016/j.forsciint.2010.04.012)

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Abstract

Expert witnesses using facial comparison techniques are regularly required to disambiguate cases of disputed identification in CCTV images and other photographic evidence in court. This paper describes a novel software-assisted photo-anthropometric facial landmark identification system, DigitalFace tested against a database of 70 full-face and profile images of young males meeting a similar description. The system produces 37 linear and 25 angular measurements across the two viewpoints. A series of 64 analyses were conducted to examine whether separate novel probe facial images of target individuals whose face dimensions were already stored within the database would be correctly identified as the same person. Identification verification was found to be unreliable unless multiple distance and angular measurements from both profile and full-face images were included in an analysis.

Item Type: Article
Additional Information: [1] Available online 31 May 2010. Published in Forensic Science International, Volume 200, Issues 1–3, 15 July 2010.
Uncontrolled Keywords: identification, CCTV, face mapping, facial comparison, anthropometry
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Pre-2014 Departments: School of Health & Social Care
School of Health & Social Care > Applied Psychology Research Group
School of Health & Social Care > Department of Psychology & Counselling
Related URLs:
Last Modified: 14 Oct 2016 09:13
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
URI: http://gala.gre.ac.uk/id/eprint/5199

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