Forensic Facial Analysis

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Evison, M.P. (2014). Forensic Facial Analysis. In Bruinsma, G. and Weisburd, D. (eds), Encyclopedia of Criminology and Criminal Justice, New York: Springer, pp 1713-29. ISBN 978-1-4614-5689-6

This text is the Accepted Manuscript. The final volume can be found here.


http://www.springer.com/gb/book/9781461456896

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Forensic Facial Analysis

Martin Paul Evison, Ph.D. Director, Northumbria University Centre for Forensic Science

Northumbria University July 2012

Prepared for Springer Encyclopedia of Criminology and Criminal Justice

Overview

Closed-Circuit Television (CCTV) systems, digital cameras, webcams and mobile

devices are the source of a burgeoning number of facial images used in criminal

investigations and prosecutions. Given the significance of facial identification to the

Courts—as well as to cases involving questioned identity documents, and border control

and immigration disputes—it is important that the strengths and weaknesses of methods

used are properly understood.

Identification of an alleged offender is fundamental to the judicial process. Courts rely

heavily on eyewitness evidence of identification and they continue to do so where facial

images are concerned. Evidence of identification, however, is widely acknowledged to be

problematic. Procedures and processes intended to make identification more reliable—

whether for use in investigation or in court—are perennial challenges.

Where facial image evidence is in issue, eyewitness evidence of investigators or other

witnesses familiar with the suspect may be given. Alternatively, expert opinion of facial

image analysis may be adduced. As well as being susceptible to the general weaknesses

of eyewitness identification, the methods of facial image analysis are susceptible to

biases known to affect other opinion evidence. The methods of facial image analysis are

scientifically rudimentary, and are as distinct from computational biometrics as they are

from the other ideals of human identification: fingerprints and DNA.

Main Text

Identification of Offenders

It is almost self-evident that for a criminal prosecution to take place an accusation must

be made against a particular individual. The prosecution must prove beyond reasonable

doubt that the offence was committed and the accused committed it. Identification of the

offender becomes a fact in issue when the accused denies they were the individual

concerned. The onus is on the prosecution to prove it was.


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Identification of Repeat Offenders

It is easy to suppose that before the advent of fingerprinting and forensic DNA profiling,

the only evidence available to establish identity from physical appearance was eyewitness

evidence, but this is not the case. In the late nineteenth century, Alphonse Bertillon

(1853-1914) pioneered measurement of body shape—anthropometry—for the purposes

of forensic human identification (Bertillon 1885). Bertillon was a pivotal figure in the

development of forensic science and facial comparison was a substantial component of

his technique. The method—coined Bertillonage—involved measurement of a set of

bodily dimensions, including those of the head and ear (Figure 1). The method also

incorporated classification of facial features, including the colour of the iris (Figure 2);

the shape of the forehead, chin and nose (Figure 3); shape of the ear (Figure 4); and style

of hair and beard (Figure 5). The nature and position of distinctive marks on the face

were meticulously documented (Figure 6) as part of a recording system which also

established early standards for forensic photography.

Despite its widespread adoption, Bertillonage was abandoned in the early twentieth

century in favour of dermatoglyphic fingerprinting. This method of human identification

was faster, less error prone, required less equipment and training, and could be applied to

marks left at a crime scene (Cole 2001).

Eyewitness Identification

If anthropometric measurement and systematic classification was discarded in favour of

fingerprinting, then how are people identified from facial images and appearance in the

criminal justice system?

Not surprisingly, individuals depicted in images are very often identified via eyewitness

evidence of some kind. In the London Riots of 2011, for instance, many of suspects were

recognised from CCTV footage. In these investigations, most suspects were identified by

members of the public. Some police officers, however, are regarded by the Metropolitan

Police as ‘super recognisers’ on the basis of their ability to identify persons already

known to them in CCTV footage using facial appearance and other cues. These apparent

talents have been widely reported in the press (Grimston 2011; Jon 2009).

Forensic Facial Image Analysis

If eyewitness evidence is unavailable or inadequate, the methods of forensic facial image

analysis may be applied. Three methods of facial image comparison are typically used in

forensic investigation. They are photogrammetry or ‘facial mapping’ (Figure 7), image

superimposition (Figure 8), and anthroscopic or morphological analysis (Figure 9).

Each of these methods requires an image of the offender—the questioned image—and a

suspect image with the faces captured from the same or a very similar angle. The

offender image may be obtained directly from digital closed-circuit television (CCTV),

video or still cameras, cell phones and similar devices. Offender images also continue to

be extracted from legacy analogue videotape systems or scanned from photographs.

The offender image should ideally be the original. Alternatively, an unaltered copy can

be used. There are a number of processes that have the potential to affect the fidelity of

the copy, most notably digital image compression. Image compression may alter the


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image and may be ‘lossy’, leading to a forfeiture of information that cannot be restored.

Lowering the resolution of images leads to pixilation of points and features rendering

them difficult to identify, classify and measure. Digital capture or scanning of analogue

images also has the potential to alter them. For these reasons, uncompressed copies at the

highest possible resolution are desirable.

Since the pose angle of the offender in the questioned image cannot be altered, some

effort can be made to capture an image of the suspect at the same pose angle—sometimes

using the original imaging system in situ at the scene. Precision is very difficult to

achieve, however, and pose angles of offender and suspect rarely match exactly.

The systems used to capture offender and suspect images may also affect the precision

that can be achieved in a comparative analysis. The processes of digital and analogue

recording are different, and in either case lens distortion, focus and lighting may affect

offender and suspect images differently.

Working from a presumption of innocence, if no explicable differences between offender

and suspect images are identified then the facial images are assumed to originate from

two different individuals and an ‘exclusion’ can be made. Explicable differences may be

attributed to factors such as pose angle, lighting, lens distortion, focus, image resolution

and compression discussed above or due to other factors such as facial expression,

ageing, trauma or surgery, hair style, clothing and jewellery, and so forth. These are

sometimes referred to as the ‘confounding factors’ of forensic facial comparison.

If no explicable differences can be found, further comparisons using one or more of the

methods of forensic facial image analysis may be undertaken.

Facial mapping and image superimposition require that the images be rotated into

alignment and adjusted to the same scale. Good practice dictates that it is the suspect

image that is adjusted in order that the offender image is unaltered. Changing the

proportions of the image invalidates the process of comparison, however, as one of its

aims is to assess whether or not the two facial images share the same proportions. By

implication, the scaling process would obscure any real difference in size between the

heads of offender and suspect, should it occur.

Although ‘facial mapping’ is known technically as photogrammetry, the implication that

it involves detailed or complex mathematical analysis is misleading. The method simply

consists of drawing parallel lines through points on features in the offender and suspect

images, in order to compare their positions and the proportions of the face (Figure 7).

Image superimposition involves the overlaying of offender and suspect images in order to

perform a subjective assessment of similarity. The most common approach involves

altering the visibility of the overlying image, gradually revealing the underlying one

(Figure 8). An alternative used in analogue systems is a ‘wipe’, in which the overlying

image is sequentially cropped from one side to gradually reveal the underlying one. A

further alternative is a ‘blink’, achieved by rapidly switching the overlying and

underlying images. In each case, it is anticipated that the eye will detect subtle

differences between the two images.


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Morphological analysis or anthroscopy (Figure 9) involves making a systematic

assessment of the shape of the head, face and facial features. Photographs or digital

images can be used. A grid may be used to guide comparison.

If—after facial image analysis—no explicable differences can be found, the images may

be said to ‘match’. Normally, a further assessment is required to judge the extent to

which the ‘match’ supports the proposition that the faces in the offender and suspect

images are from one and the same person.

The UK Forensic Imagery Analysis Group (FIAG) advocate a sliding scale of support

(Bromby & Plews 2006), with criteria for assignment to each level on the scale (Table 1).

The Court is usually provided with a statement describing the analysis and the expert’s

view as to the strength of support it affords for the assertion that the facial images

depicted are from the same individual. Recently, experts have qualified their opinion by

stating matching evidence may arise from the defendant or someone of similar

appearance.

Bertillon (1885) appears to have perceived this issue. Distinguishing dissimilar faces is

frequently trivial. Distinguishing similar faces is the real problem. Other than the author’s

own image, the faces given in the examples in Figures 7 to 9 are those Bertillon chose to

illustrate the problem of distinguishing similar faces. In two of the three examples the

images originate from the same individual, in one exceptional example they do not.

Current Issues and Controversies

Facial image analysis remains a subjective process sometimes supported by a technical

method and then only in part. Psychological studies have raised issues concerning the

reliability of face recognition and of cognitive bias in comparative forensic analyses.

Reviews of the effectiveness of forensic science have questioned the scientific basis of

many forensic science sub-disciplines as well as the subjective paradigm from which the

forensic identification sciences operate.

The Psychology of Face Recognition

While face perception and face recognition remain exciting subjects of academic inquiry,

certain features of our ability to perceive and recognize faces are clear. People are very

good at recognizing familiar faces and very bad at recognizing unfamiliar ones. Using

standardised sets of photographic images called face pools (Figure 10), researchers in

psychology (Bruce et al. 1999) demonstrated the highly error prone nature of recognition

of unfamiliar faces. Kemp et al. (1997), for example, attached small photographs of

shoppers to credit cards and asked cashiers to confirm that they belonged to the bearer.

The subjects were able to detect fraudulent cards in only 36 per cent of trails when the

photograph bore some resemblance to the bearer and in 66 per cent of trails when the

photograph bore no resemblance.

Familiar faces are, in contrast, reliably recognised from face pools.

The same pattern is evident when reliability is assessed using CCTV footage of familiar

and unfamiliar subjects. Burton et al. (1997) showed familiar individuals can be

recognized quite reliably even from poor quality CCTV footage, but unfamiliar subjects

are frequently misidentified. The performance of students and police officers was


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similarly poor. Bruce et al. (1999; 2001) also demonstrated the highly error prone nature

of recognition of unfamiliar faces from CCTV images and video stream.

Error in Eyewitness Identification

The findings of Bruce and other psychologists of face perception offer scientific

confirmation of the potential danger of eyewitness identification long recognised by the

courts. Cases of mistaken identity—particularly of individuals unfamiliar to the

witness—have become seminal in reforms of judicial procedure. In England and Wales,

the Turnbull guidelines—arising from R v. Turnbull 1977 (QB224 CA)—govern the

circumstances and nature of warnings to the jury of the risks inherent in eyewitness

identification. Similar procedures are followed in US courts—see Watkins v. Soders 1981

(449 US 341; 101 SCt 654).

Both psychologists and the courts accept that eyewitness identification can be dangerous

when unfamiliar faces are involved. Psychological evidence indicates that recognition of

familiar faces is quite reliable, but it certainly is not perfect. A celebrated English case

from the nineteenth century involves that of Adolf Beck (Anon 1999), a man who had the

misfortune to resemble fraudster Wilhelm Meyer, who presented himself to his victims as

Lord Willoughby. One of Meyer’s victims mistook Beck for Meyer. Beck’s misfortune

was compounded when ten or eleven of Meyer’s other victims also did so. Two police

officers familiar with Meyer also identified Beck as Meyer. One, Eliss Spurrel, stated

“There is no doubt whatever he is the man. I know what’s at stake on my answer, and I

say without doubt he’s the man”. Having been found guilty not once, but twice of crimes

committed by Meyer, Beck was awaiting sentencing when Meyer himself was arrested.

The mistaken identity—and the passing resemblance of the two protagonists (Figure

11)—finally came to light and Beck was pardoned.

A further case arose in England in the twentieth century, which involved the mistaken

identity of Laszlo Virag as armed thief Roman Ohorodnyckyi—also known as Georges

Payen (Figure 12). In the Virag case (Devlin 1976), a number of witnesses including

police officers again mistook Virag for Payen and confidently so. One officer, Police

Constable Smith, stated “his face is imprinted on my brain”. Virag was convicted, but

items subsequently found in Payen’s possession, including the relevant firearm, led to

Virag’s exoneration, the Devlin Report (1976) on identification in criminal cases and the

adoption of the Turnbull guidelines .

Cognitive Bias

The findings of Bruce and other psychologists of face perception offer scientific

corroboration for the premise that humans are good at recognising familiar faces, but

poor at recognising unfamiliar ones. Other psychological studies support the proposition

that some individuals are exceptionally good at face recognition (Russell, Duchaine, &

Nakayama 2009). Humans are, unfortunately, susceptible to other cognitive biases that

can lead witnesses, including police officers, to mistakenly—if honestly—make highly

confident, but erroneous identifications from facial appearance.

The wrongful convictions of Adolph Beck and Laszlo Virag each led to changes in the

English court system and—in order to prevent errors and pre-empt courtroom


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challenges—to changes in police procedures relating to identification from arrest

photographs and identification parades.

The risks of context and confirmation bias in forensic comparisons have been well

rehearsed by Dror (Dror, Charlton, & Peron 2006) in relation to fingerprints, and similar

dangers apply to identifications from CCTV and forensic facial images. Video

superimposition is a particularly subjective technique, with the capacity to obscure

differences rather than reveal them.

Scientific Basis of Forensic Facial Image Analysis

Forensic facial image analysis is scientifically rudimentary. There is a small literature

(Porter & Doran 2000; Vanezis & Brierley 1996; Vanezis et al. 1996; Yoshino et al.

2000) supported by guidelines published in the US (SWGIT 2012) and UK (ACPO

2009). Validation studies are almost unknown. There is no reported error rate for forensic

facial image comparison, whether conducted by police ‘super recognisers’ or ‘facial

mapping experts’.

There is no scientific basis for assigning the weight of a comparison against a sliding

scale of support. This is a matter of subjective opinion. Two experts could disagree and

both be ‘right’—see Mallett and Evison (2012). This is a position that is hardly tenable in

science. The limited scientific basis of forensic facial image analysis is discussed in

further detail by Edmond (Edmond 2011) in relation to courtroom admissibility of facial

comparison evidence. The UK Court of Appeal held in R v. T (ECWA Crim 2439; 2010)

with regard to footwear impressions that the expert should not use the word “scientific”

where it gives an impression to the jury of a degree of precision and objectivity that is not

present. This caution is equally warranted with regard to facial image comparison and is

all the more important giving the compelling nature of facial image evidence.

Conclusions and Future Research Despite the ubiquity of the face as the primary mode of recognition in humans and the

increasing prevalence of facial images, most forensic identifications are based on

eyewitness evidence of some form. Forensic facial comparison is not scientific, and the

scientific claims of facial mapping and image superimposition are tenuous. There are

presently two significant drivers of potential change, however, that may lead to the

development of a forensic science of facial image analysis. These are the systematic

investigation of images from CCTV footage and the expectation for increasing scientific

rigour in the forensic sciences.

Systematic Use of Images in Criminal Investigation

The investigation of the London Riots of 2011 is notable for the extensive

implementation of a thorough and systematic approach to the investigation of images

from CCTV and other sources—digital cameras and other mobile devices. This approach

was based on pre-existing Visual Images Identification and Detection Office (VIIDO)

units introduced by Michael Neville of London’s Metropolitan Police Service (Grimston

2011). Not only do these units control collection and analysis of image evidence, they

ensure that it is supervised and actioned (Jon 2009). Online and mobile (APCO 2012)


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apps are offered to support dissemination of images captured from CCTV and other

sources.

The paradigm shift in forensic science

The unparalleled success and reliability of forensic DNA profiling has led to a postulated

‘paradigm shift’ in forensic science (Saks & Koehler 2005), which predicts that more of

the forensic science sub-disciplines will need to follow the model offered by DNA. Both

the United States National Research Council (NRC 2009) and the UK Forensic Science

Regulator (Rennison 2008) call for forensic science to be based on sound scientific

methodology, logical and statistically supported interpretation methods, and known error

rates. Biometric technology may offer some value to forensic facial comparison, but at

present the value of automated systems is investigative and not probative (Dessimoz &

Champod 2007; Evison 2011). Reliance on automated biometric systems may also lead to

a new kind of complacency that promotes context bias (Dror & Mnookin 2010).

Some research, such as that of Mardia et al. (1996), Yoshino et al. (2000) and Evison et

al. (Evison et al. 2010; Evison & Vorder Bruegge 2010) has explored the potential for

measurement-based and probabilistic methods of facial comparison using features

demonstrable to a lay person. This approach is provisionally able to distinguish the

famously similar appearances of Will and William West (Figure 12), an early case of

persons distinguished and identified from their fingerprints by the FBI.

Presently, however, investigation relies on recognition from CCTV images and

prosecution on the admissibility of eyewitness identification as evidence in court.

Although some investigators coin CCTV image analysis the third forensic discipline (Jon

2009) after dermatoglyphic fingerprinting and DNA analysis, the allusion is somewhat

misleading as there is no definitive forensic science of facial image comparison.

References

ACPO. 2009. Facial Identification Guidance. London: Association of Chief Police

Officers. http://www.acpo.police.uk/asp/policies/Data/Facial%20ID.pdf (accessed

20th July 2012).

Anon. 1999. The strange story of Adolph Beck. London: Stationery Office.

APCO. 2012. Public encouraged to identify criminals with mobile app. British

Association of Public Safety Communcations Officials Journal. July 2012.

http://www.bapcojournal.com/news/fullstory.php/aid/2239/Public_encouraged_to

_identify_criminals_with_mobile_app.html (accessed 30th July 2012).

Bertillon, A. 1885. Identification anthropométrique: Instructions signalétiques: Paris:

Melun.

Bromby, MC, and S Plews. 2006. Guidance for Evaluating Levels of Support. FIAG:

Forensic Imagery Analysis Group.

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familiar and unfamiliar faces caught on CCTV images. Journal of Experimental

Psychology-Applied 7 (3):207-218.

Cole, S. 2001. Suspect identities: a history of fingerprinting and criminal identification.

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and R. W. Vorder Bruegge. 2010. Key parameters of face shape variation in 3D in

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Table 1. Sliding scale of support (Bromby & Plews 2006)

No

Support

There are no significant differences observable, from which to eliminate; and there may be a

number of similarities. The imagery evidence is too poor to permit observation in either

direction.

There may be very general characteristics observable (i.e. race, gender, hair colour), but

these do not offer enough support towards specific identity.

Limited

Support

There are a few general characteristics observable. In combination, these provide a low level

of facial uniqueness.

The image quality does not permit observation of individual facial feature detail (or only

very limited detail).

The facial geometry may or may not be matching, but observation of identifiable landmarks

is restricted by the image quality.

Moderate

Support

There are a few general characteristics observable.

The image quality permits observation of a moderate amount of facial feature detail; i.e. for

each visible feature one to a few descriptives can be provided. For example, the nose could

be classified as having a narrow bridge and a straight ridge.

In combination, a moderate level of uniqueness is available for the facial features.

The facial geometry may be matching, but observable detail is moderate (observation of

identifiable landmarks is somewhat restricted).

Support

The image quality permits observation of individual facial feature detail to some extent.

There are a few facial features observable.

There may or may not be matching geometry, but this is limited to one or two instances.

In combination (or alone), the facial features have an average amount of uniqueness; they

are shared by an average number of people.

The facial similarities can be observed a few times. This may be in combination.

The face is observable from only a few differing viewpoints.

Strong

Support

The image quality permits a good level of individual facial feature detail to be observed.

A high number of facial features are observable.

In combination (or alone), the features provide a reasonably high level of uniqueness.

The facial geometry may be matching and multiple landmarks are observable from which to

align.

The similarities can be observed a reasonably good number of times.

The face is observable from multiple differing viewpoints

Powerful

Support

A very high number of facial features are observable.

The image quality permits a very good level of facial feature detail to be observed.

In combination (or alone), the features provide a high level of facial uniqueness. In the case

of the ear, multiple points can be observed to be matching.

The facial geometry is matching on several occasions.

The facial similarities can be observed alone or in combination a high number of times.

The face is observable from multiple viewpoints allowing for a pseudo-three dimensional

impression of the face.


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Figure 1. Standard measurements of the head and ear adopted by Bertillon (1885).

Figure 2. Standardised references of iris pigmentation adopted by Bertillon (1885).

Figure 3. Standardised references for the shape of the nose (Bertillon 1885).

Figure 4. Standardised references for the shape of the ear (Bertillon 1885).

Figure 5. Standardised references for the shape of the beard (Bertillon 1885).

Figure 6. Standard classification of distinguishing facial marks (Bertillon 1885).

Figure 7. Illustrative example of facial comparison by photogrammetry. Typically, a

series of parallel lines are drawn between common features in offender and suspect

images, such as the pupils, the commissure of the mouth and the facial midline. If the

lines are congruent and no explicable differences between the facial images can be

identified the expert may conclude the images come from the same individual or—more

circumspectly—another individual of similar appearance.

Figure 8. Illustrative example of facial comparison by video superimposition. Images

have been superimposed using Adobe® Photoshop® with the opacity of the

superimposed image gradually reduced to reveal the underlying one. Again, if no

explicable differences between the facial images can be identified the expert may

conclude the images come from the same individual. Video superimposition involves no

explicit measurement, and its subjective nature is compounded by potential neurological

(persistence of vision) and psychological (context bias) influences on the examiner.

Figure 9. Illustrative example of facial comparison by anthropscopy. Anthroscopy or

morphological analysis involves the systematic comparison of the shape of the facial

features and other distinguishing marks. Although subjective, anthroscopy can rely on the

use of classical anatomical classification and descriptive terminology that is open to

confirmation or dispute. Descriptive classifications may include, for example, the shape

and position of the inner and outer canthi (commissures of the eyelids), chelions

(commissures of the lips), alares (nostrils), attachment and shape of the ear lobes, and

shape and prominence of the chin.

Figure 10. Example of an experiment in facial recognition (Bruce et al. 1999) using a

face pool. The subject is invited to establish whether or not the target face (upper image)

is present in the array and, if so, which one it is.

Figure 11. Images of Adolph Beck (upper) and Wilhelm Meyer (lower). The Adolph

Beck case was contributory to the development of the Court of Appeal in England and

Wales.


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Figure 12. Images of Laszlo Virag (left) and Roman Ohorodnyckyi or Georges Payen

(right). The Virag case ultimately led to the adoption of the Turnbull guidelines in

England and Wales.

Figure 13. Images of Will and William West, inmates of Leavenworth Penitentiary in the

United States who shared the same name, had similar facial appearances and could not be

distinguished by the Bertillon system. Will and William West were distinguished using

fingerprints, however. Note also that their facial proportions (see superimposition, right)

and ear shapes are also different.


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