Face Recognition

1. Face Recognition • The following slide has photographs of people. • Try to identify the people. • You may not recognise all of them. • If you can’t identify them, do you perhaps know anything about one of them? • Write down your answers. Do it completely on your own to get the best benefit from the exercise

3. Face Recognition • Now, choose any one of the faces, whether it is one you know or one that you are unfamiliar with, and write a description of that face. • Again, do this on your own.

4. Here are the pictures again – ask your neighbour how well you did.

5. Face Recognition • Turn to page 320 in Pennington. Read the study by Bahrick, and briefly state: • Aim – Method – Results – Conclusion

6. Bahrick - continued • Difference between recognition and identification over time also investigated. • Table page 320.

7. Application of Bahrick: • Important application of face identification research is in crime detection – e.g. photofits. • Photofits are based on forward facing, stationary images. • Bahrick showed that identification is best when actual person is there. Can’t always do that, so what could be an alternative to photofit that would be more efficient?

8. Ripper Images

9. Ripper Images

10. Photo identification • Bahrick showed that identification is best when actual person is there. Can’t always do that, so what could be an alternative to photofit that would be more efficient? • Modern methods use video technique. Instead of flat pictures, composite video images are prepared with the witness. Seems to be an improved success rate.

11. Feature Analysis • P 321 Pennington • Look up description of photo you made earlier • Shepherd, Davies & Ellis (1981) – free recall recognition test. • Mainly features described/recalled

12. Feature recall Hair Nose Eyes Mouth Chin eyebrows Forehead

13. Shepherd Davis & Ellis showed that features are usually recognised in the order given in the Previous slide. Descriptions of faces fit in more with externalfeatures, but when we know the person, we useinternal features. How do your descriptions fit in with this feature detection theory? Feature detection is a theory based on recognitionof individual features. The combination of the featuresproduces a whole image with meaning. Question: Top–down or bottom–up theory? Gollum

14. Holistic-form Theory P322 Pennington. • Generally recognised that facial recognition is more complicated than simple feature analysis • See someone you know in the street, need to refer to previously stored knowledge about the person • Top-down or bottom-up?

15. Holistic-form theory suggests that face is recognised as a whole (holistic = • based on the whole) by analysis of • relationship between features • feelings aroused by the face of each person we know • semantic information about the person (e.g.a name?) Ellis suggests we have a facial template for each person we know. We see them and match data with the template. This is Top-Down

16. Holistic-form processing – Young and Hay (1986)

17. Holistic-form processing – Young and Hay (1986)

18. Holistic-form processing – Young and Hay (1986) • Renee Zellweger and Liv Tyler • But Composites are not so easy to identify • Feature analysis – would be just as easy to identify composites if only features are used

19. Holistic-form processing – Young and Hay (1986) • But Holistic-form would suggest it is harder to identify composites because we are in effect making a new face out of the parts. • Similar effects with cut up and upside down bits of faces • Be Amazed!!

22. That was George Bush as we’ve never seen him! It is known as the Thatcher Illusion – guess why…

24. The moral of the story is • If you want to rob a bank, get a wig!

25. Application to Investigation of Crime • Photofit – based on building up face from individual features. • Operators intensively trained. • When they tried to train potential witnesses… • Feature training resulted in poorer performance • Suggestion is… • Faces are stored holistically rather than by features

26. Familiar Face

27. Familiar Face Structurally encoded A mental description Or representation of The face is produced From the stimulus

28. Familiar Face Structurally encoded A mental description Or representation of The face is produced From the stimulus Activates Face Recognition Unit (FRU) Each face known to the viewer has FRU containing Structural information About the face.

29. Familiar Face Structurally encoded A mental description Or representation of The face is produced From the stimulus Activates Face Recognition Unit (FRU) Each face known to the viewer has FRU containing Structural information About the face. Activates Person Identity Node (PIN) Information about the person, e.g. occupation, usual context, Do I like him/her, etc.

30. Familiar Face Structurally encoded A mental description Or representation of The face is produced From the stimulus Activates Face Recognition Unit (FRU) Each face known to the viewer has FRU containing Structural information About the face. Activates Person Identity Node (PIN) Information about the person, e.g. occupation, usual context, Do I like him/her, etc. Activates Name Generation Name is stored separately, Accessed last. (TOT State?)

31. Young, Hay and Ellis (1985) • Pennington page 325 • Aim – Method – Results – Conclusion

32. Young, Hay and Ellis (1985) • Aim – to test holistic model • Method – diary study • Results – (i) no reports of naming without prior information. (ii) some cases, (19%) occupation but not name. (iii) more cases, (23%) familiarity, but no more. • Conclusion – supports holistic model sequence.

33. Recognition Disorders • Prosopagnosia – very rare – can’t recognise familiar faces. Own reflection? • Sufferers get vague emotional feeling of recognition (I ought to know them!) but no conscious awareness of knowledge.

34. Recognition Disorders • Capgras syndrome • “Doubles have replaced people I know” • Recognition, but emotionally, it is not the person. • Tested by GSR emotion response. • No difference between friends and strangers

35. Recognition Disorders • What conclusion from disorder studies? • Face recognition depends on more than just face patterns. • So, Holistic model is more likely. • Implication in e.g. identity parades.