Face recognition in applied context Flashcards
Why are faces important? (4)
We use faces to help us to establish age, gender, and mood
Identification
Attractiveness
Emotional Expression
How is face recognition separate from object recognition? (3)
Faces are dynamic
Different neurological pathways and processes
Prosopagnosia
Identification of familiar faces is generally very good under which conditions? (4)
Lighting changes
Disguises
Viewpoints
Expressions
What are the problems in unfamiliar face recognition? (5)
Viewpoint – much of the research has focused on frontal views of faces but faces are 3-D and complex
Profile is particularly bad especially when generalising from one profile to another
Viewpoint changes have a particularly large effect on unfamiliar faces
Profiles obscure much of the configural information that seems to be important
Inverting a face also makes recognition difficult
Why is 3/4 view best recognised? (2)
Partly because this lies between frontal and profile so any change (learning – test) is relatively small
When is profile view particularly bad? (1)
Profile is particularly bad especially when generalising from one profile to another
How do negative and lighting effects impact face recognition? (4)
Negatives are very hard to recognise
Representations must encode more information than this from the original image – hence the difficulty
It is the loss of shading that causes difficulty in recognising negatives
Lighting an image from below has a similar effect to negation and also disrupts identification
What information can negatives provide? (2)
Position and size of facial feature
What is configuration? (1)
The relationship between different components of a face
Why does inverting face cause problems with facial recognition? (3)
Makes viewers less sensitive to configures information compared to upright faces
- causes loss of configural information
- Thatcher illusion (Thompson, 1980)
- inversion effect is greatest with faces compared to houses or other objects
What is Bartlett and Searcy (1993) do and what did they find? (2)
Made unreasonable configural adjustments
However, ‘grotesqueness’ ratings were much lower when the faces were inverted
How are distinctive faces recognised? (3)
Distinctive faces are more likely to be remembered and more quickly recognised if distinctive
How are caricatures recognised? (3)
Caricatures are recognised more quickly than ‘true drawings’
Caricaturing improved recognition in typically poor settings
Caricatured photographs may be rated as a better likeness of the face than the actual photograph
What influences recognition? (7)
Distinctiveness / Familiarity
Disguises – covering the hair, sunglasses because these features are important in recognition
Carragher & Hancock (2020) reported the surgical masks have a detrimental impacton matching faces
Wells and Olson (2003) noted that light levels should influence recognition andhence EWT accuracy
Length of exposure to culprit although ‘weapon focus effect’
Also if abstract judgements are made then recall of the face is better
Changes over time – facial hair / ageing
Are some witnesses better than others? (5)
Gender – small effect, but overall very little difference
Age
Intelligence
Race
Little evidence that personality is a factor though anxious make fewer mistaken ID’s
How does gender of witness impact face recognition? (3)
Small effect, but overall very little difference (Shapiro & Penrod, 1986)
Some advantage for females
Haj et al. (2019) reported that single males showed an advantage for recognition of female faces compared to in-relationship males or females (any status)
How does age of witness impact face recognition? (2)
Young and old make errors – mainly when the culprit is absent
Brackmann et al. (2019) reported more bystander errors in adolescents than adults and children
How does intelligence of witness impact face recognition? (2)
Shakeshaft & Plomin (2015); Gignac et al. (2016) found a correlation, but others found no relationship
How does race of witness impact face recognition? (3)
Better memory for faces from the same race - own race bias.
Recent research has shown that this is due to early processing as the effect also exists in visual working memory
Stelter & Degner (2018); Burgund (2021) found evidence of different eye fixations for different race faces
What are the problems with traditional measures of retrieval? (2)
Mug shots can cause interference
Photo / in-person line-ups can be biased
How are traditional measures of retrieval improved? (5)
Double blind procedure
Witness told that procedure is double blind
Suspect should not stand out
Statement of confidence taken prior to any feedback
Told that culprit may or may not be present
What are the problems with using CCTV footage for facial recognition? (3)
They may be:
Very small
Poor quality
Taken from strange angles
Badly lit
Describe Henderson, Bruce and Burton, 2001 study (1)
Participants were required to match CCTV images to a face from a choice of 8 ‘mug-shots’
What did Henderson, Bruce and Burton, 2001 study find (7)
Pooling first and second choices gives a mean accuracy (for both ‘robbers’) of 28.5%
Better than chance but some faces were chosen more frequently than the actual robber
Matching faces from poor quality CCTV is clearly difficult
Matching photos to photos improves to 76% for Robber 2 (33% for Robber 1)
Still high error rates and other faces are still frequently selected
Matching of unfamiliar faces is difficult even with quality images
Mileva & Burton (2019) confirm that CCTV images remain poor at times
