The mention of facial composites often conjures up images of a sinister criminal, skillfully depicted by a sketch artist using pencil and paper. In reality, the vast majority of law enforcement agencies use mechanized methods, usually computer software, when creating facial composite. By having a vast repertoire of eyes, ears, hair and so on at their disposal, witnesses have the ability to create an image that ideally encompasses all of the features of the perpetrator. So have these technological advances improved our ability to identify and apprehend criminals Gary Wells and Lisa Hasels of Iowa State University say \"no.\"
In an article appearing in the February issue of Current Directions in Psychological Science, the authors point to several studies that indicate facial composite systems produce a poor likeness of the intended face. For instance, studies in which individuals attempt to create composites of celebrities have yielded extremely poor results. In one particular study, only 2.8 percent of participants correctly named a well-known celebrity that had been created by other participants using the face-composite software. In a separate study, participants were unable to discriminate composites of their classmates from composites of students at entirely different schools.
According to authors, these poor results are not deficiencies in the software per se but instead a mismatch between how we remember faces and how composites are produced. \"Numerous lines of evidence converge on the view that faces are generally processed, stored and retrieved at a holistic level rather than at the level of individual facial features.\" Ultimately the psychological process of remembering faces may include more complex representations such as multidimensional similarity to other faces or relative sizes and distances of features and so on that are not readily retrieved by memory nor utilized by facial composite software.
The knowledge of holistic processing may be a boon to future face-composite systems that will utilize \"whole-face\" methods for face recall. Such systems begin by generating a random set of faces and the witness selects the face most similar to their memory of the perpetrator. This will be the \"parent\" face that yields a set of similar looking faces that are the result of several mutations to the parent face. The witness again makes their choice and the process continues until they can no longer discriminate their options from their memory of perpetrator. Although in its nascent stages, preliminary tests demonstrate whole-face systems to be superior to their traditional composite counterparts.
Attempts to evaluate and improve face composites fit into the larger problem of the criminal justice system, say the authors. Analyses of the first 180 DNA exonerations to occur in the United States revealed that mistaken eyewitness testimony was involved in 75percent of the cases. Guilty suspects may likewise be comforted or encouraged by poor composites poor composites that lead crime investigators towards innocent parties, says Wells. \"Imagine the solace of the culprit who sees a composite of his face in the newspaper that looks nothing like his face.\"
Thus an increasing knowledge of the memory processes involved in facial recognition will help to improve the accuracy of facial composites and ultimately reduce the number of innocent convictions. Simply put, \"as the historical and natural home of the science of memory, psychological science has great promise for helping to solve an age-old problem.\"
EvoFIT is an award-winning system for constructing facial composites of offenders by witnesses and victims of crime. It is currently being used by police forces in the UK and overseas with great success.
Once a potential suspect has been identified by the police, they may ask the composite-creating witness to view that suspect in a line-up or identity parade. Some research has found that composite creation enhances identification accuracy, when performance is compared with non-composite creating controls e.g., 11-12. Other research, primarily employing feature-based systems has found that composite creation negatively impacts identification performance e.g., 7, 9-10. If a composite is a poor likeness to the culprit, identification accuracy appears most susceptible 8, 10. This suggests that for creating witnesses, a facial composite may provide a more salient memory trace than that of the original suspect. Nevertheless, all other things being equal, the chances of a correct identification should be enhanced by the creation of a holistic system composite, as these are likely to be closer in likeness to the culprit than a feature-based composite.
Figure 2. Facial composite construction method A: Face shape. At this stage in the facial composite construction procedure, after the operator enters basic description keywords into the holistic composite system, the participant-witness is asked to select an approximate face shape meeting their memory of the culprit from the nine images displayed on the screen, or to reject that array to produce a new display. As with the reminder of the construction process, this stage assesses recognition (see 2.9.1). Please click here to view a larger version of this figure.
Figure 3. Facial composite construction method B: Hairstyle tool. Following selection of face shape, and facial features, the participant-witness is asked to select an approximate hairstyle from the nine images displayed on the screen, or to reject that array to produce a new display. The default hairstyle on all images is grey, until coloring is added (see 2.9.3). Please click here to view a larger version of this figure.
Figure 4. Facial composite construction method C: Shoulders tool. Following selection of face shape, and facial features, the participant-witness is asked to select shoulders from the nine images displayed on the screen, or to reject that array to produce a new display. Clothing color and style can be manipulated and company logos or other idiosyncratic features may be added (see 2.9.4). Please click here to view a larger version of this figure.
Figure 6. Facial composite construction method E: Holistic attributes tool. The participant-witness may also suggest changes to the holistic properties of the selected face (e.g., age, distinctiveness) by using a slider tool. Again, the outcome is compared to the original unmodified image on the screen (see 2.9.8). Please click here to view a larger version of this figure.
Figure 7. Facial composite construction method F: Final image. In a police investigation this image would be printed, and a copy transferred to CD to be retained in the evidence bag (see 2.9.9). Please click here to view a larger version of this figure.
Figure 8. Video lineup stills. (A,Please click here to view a larger version of this figure.B) Frontal and profile facial image stills of the culprit in the culprit-present video line-up procedure (see 5.2). Please click here to view a larger version of this figure.
The influence of composite construction on eyewitness identification is measured by comparing the line-up selections of participant-witnesses and controls. Table 3 displays representative results taken from a subset of the data collected in Experiment 1 of 11 in which control line-up outcomes were compared with participant-witnesses who created a holistic facial composite using the system described in this protocol. The delay between viewing the initial culprit crime scene video and the video line-up in this experiment was approximately 2 hr.
The research was partly funded by an internal University of Greenwich grant to the first and third authors. Thanks go to Dominic Goodchild, Chris Hughes, Adrian Ibanescu, Corrado Ranelli, and Charlie Shaw for acting as culprit-actors in the crime scene videos, and to Henry DC Williams for filming and directing the crime scene videos. Thanks also to Detective Chief Inspector Mick Neville, Inspector Barry Burnell and Sergeant Nick Milbourn from the Metropolitan Police Service for creating and supplying the PROMAT video line-ups for the project and advising on the design and video line-up procedure. Thanks also to Detective Constable Tony Barnes of the Metropolitan Police Service for providing advice on the use of the specific holistic facial composite system in police investigations, and allowing the second author of this paper, who is the composite operator depicted in the videos, to shadow him while working with eyewitnesses to create facial composites during investigations into real crimes.
Charlie Frowd, Professor of Forensic Psychology, has co-designed pioneering software called EvoFIT, a forensic instrument that substantially outperforms previous photofit (facial-feature) type methods to help identify criminal suspects.
The EvoFIT facial composite system is used by 26 police forces in 11 countries and has helped with over 2,500 criminal investigations. The system has changed international constabulary practices and directly assisted in the identification and arrest of an estimated 1,500 serious offenders. It greatly improves on previous methods that typically only correctly identified 5% of suspects, whereas police field trials using EvoFIT composites indicate an arrest rate of 60%. The police forces using the system report that it has led to improved conviction rates for serious criminals, made changes in their knowledge and capabilities and, subsequently, changed law enforcement practice.
Facial Database With an expanded database of 4,400 facial features, including new Latin, African-American and Asian components, FACES 4.0 lets you create accurate composites of either sex and any race. Selected features are blended together to produce a photo-quality composite image. New to FACES 4.0 is the ability to enhance image accuracy by choosing among three different hair tones: adding facial markings such as scars, moles, piercings, tattoos and earrings: and using hats, headwear and eyeglasses. 153554b96e