DocumentCode
1702917
Title
Catching Even More Offenders with EvoFIT Facial Composites
Author
Frowd, Charlie D. ; Pitchford, Melanie ; Skelton, Faye ; Petkovic, Anna ; Prosser, Colin ; Coates, Brian
fYear
2012
Firstpage
20
Lastpage
26
Abstract
Facial composites are an investigative tool used by police to identify suspects of crime. Unfortunately, traditional methods to construct the face have rather low success rates. We have been developing a new recognition-based method called EvoFIT that requires eyewitnesses to select whole faces from arrays of alternatives. Both published laboratory research and existing police field-trials have found that EvoFIT produces images that are more identifiable than images from traditional systems. In the current paper, we present an evaluation of a more recent version of EvoFIT: in 2010, EvoFIT was deployed in 35 criminal investigations by Humberside police and these images directly led to identification of 21 suspects, equating to 60% success - quadruple the performance of the previous system used within the force. The evaluation also showed that identification of a suspect led to conviction in 29% of investigations (6 out of 21). Overall, a conviction occurred in 17% of cases involving use of an EvoFIT (6 out of 35). We also outline more recent developments which indicate that an arrest is now likely in three out of every four cases in which EvoFIT is used, and a conviction rate of one in five.
Keywords
criminal law; face recognition; police data processing; EvoFIT facial composites; Humberside police; conviction rate; crime suspect identification; eyewitnesses; face construction; image recognition-based method; Face; Face recognition; Force; Hair; Laboratories; Software; Standards; EvoFIT; facial composites; field test; recognition system; victim; witness;
fLanguage
English
Publisher
ieee
Conference_Titel
Emerging Security Technologies (EST), 2012 Third International Conference on
Conference_Location
Lisbon
Print_ISBN
978-1-4673-2448-9
Type
conf
DOI
10.1109/EST.2012.26
Filename
6328075
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