BRUCE AND YOUNG’S THEORY
AO1
Face recognition is a series of stages which are accessed one after another (serially) not all
units/nodes are activated at the same time. There are 2 routes through the model.
The process starts with structural encoding – details of a person’s faces are encoded and
information sent to the different units.
1. Recognising familiar faces – one route
FRU’s contain info on faces you know. If the encoded info has a reasonable match with
this stored info the unit is activated and triggers the next node – PIN. PIN’s contain
information about the persons identity e.g. occupation, interests etc. once a persons
identity is established their name can be retrieved NRU. As it is a serial access model,
names can only be accesses after the person has been identified i.e. need to know
information about the person before the name can be accessed. No direct link from
face to name. People rarely remember a name without knowing some personal
information about the person, but can know personal information and find it hard to
remember a name. Activation of any of these 3 nodes may draw on cognitive system
to decide whether match is close enough to be recognition not just resemblance.
2. Other aspects of face processing – second route
This route is concerned with other information provided by faces e.g. emotional state
or info on what a person is saying. Data from structural encoding is used to work out
meanings of facial expressions (expression analysis node), use lip movements to help
understand what someone is saying (facial speech analysis) and process other visual
information (direct visual processing). This route is used to process unfamiliar faces.
This is why some people with brain damage can match familiar faces but not
unfamiliar faces. – Malone.
All units are linked to the cognitive system which provides information about stereotypes e.g.
actresses tend to be attractive, or information about people we know. May see someone that
looks like a film star but how likely are they to be in your local (probably someone that
resembles them)
TYPE OF PROCESSING MODULE
Structural encoding
Expression analysis
Facial speech analysis
Directed visual processing
Facial recognition nodes
Person identity nodes
Name generation
Cognitive storage
DESCRIPTION OF MODULE
Creation of descriptions and representations of faces
Analysis of facial characteristics to infer emotional state
Analysis of facial movement to comprehend speech
Selective processing of specific facial data, like the colour
of the eyes
Stored structural descriptions of familiar faces
Stored information about familiar people, like their
interests and talents
Separate store for name
Extra information aiding the recognition process, like what
context individuals are known in
AO2
The model has been very influential.
Research – young conducted a diary study were 22 participants kept a record of the mistakes
they made when recognising people over an 8 week period. Many errors involved recalling
information about a person but not their name, but never recalling a name without recalling
personal identity information. Supports the serial nature of the model. People also reported a
feeling of familiarity but unable to think of any personal info – suggesting FRU activated but
not PIN.
Young also found that people were faster at identifying whether a particular face was that of
a politician than at identifying the politicians name.
However Stanhope and Cohen found that participants could retrieve names for faces despite
having no information on personal identity.
Main strength – it generates precise predictions that can be tested and further our
knowledge of face recognition. Shows the different way familiar and unfamiliar faces are
processed but the details for unfamiliar faces are vague. Role of cognitive system is unclear
and doesn’t account for the process involved in learning to recognise new faces and storing
these images in memory.
Applications – producing machines that will recognise faces for security and help police with
better eyewitness records for faces . e.g. E-FIT, Facelt (using 3D imagery) and US-VISIT.
However systems are not perfect and may never match human ability to recognise faces.
The model is continually being developed and refined.
Burton and Bruce extended the original model, developing the IAC model (interactive
activation and competition network). This is a connectionist model suggesting that face
recognition involves are a large number of nodes that have complex connections between
them (i.e. not serially linked) this is similar to how the nervous system works.
This model is only about face recognition so suggests it is special, but not that is necessarily
qualitatively different from other types of object recognition. To try and see if face
recognition is different researchers have looked at brain damaged patients.