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.