1. Horizontally split facial composites show improved identification Alex H. McIntyre, Peter J.B. Hancock and Charlie D. Frowd Department of Psychology University of Stirling

2. Facial Composites Images produced by combining separate facial features. Created with sophisticated software that are capable of generating very good likenesses. In spite of this identification rates are very poor. Important and accurate information with the composites is not readily perceived.

3. Accuracy of information Facial composites are produced from an often fleeting memory. Not all of the information they contain will be accurate. May be the only tangible clue in a police investigation. How can we capitalise on the more accurate elements?

4. Perceiving Faces Featural information. (eyes, nose, mouth etc.) Configural information. (the relative size and location of features relative to one another) Information is processed separately and differentially. In normal adult face perception configural information tends to dominate.

5. Effects of Inaccuracy Featural inaccuracies are easier to discern. Configural inaccuracies are much more subtle but exert profound effects. They can actually inhibit recognition of accurate facial features. An inaccurate configuration can even be perceived as a completely new face.

6. Configural inaccuracy in facial composites 32 original composites. 32 configurally enhanced (morphed) composites. 32 participants viewed 16 of each, with each target represented once. Conditional hit rate.

7. An original composite and a morphed composite of Brad Pitt 16.6%32.4% t(31) = 6.45, p<.001.

8. Results Configural inaccuracy does have a significant effect on the identification of facial composites. How can we reduce the effects of configural inaccuracy in an applied setting?

9. Young, Hellawell, & Hay (1987)

10. Getting easier?

11. Young, Hellawell & Hay (1987)

12. Continued….

13. Young, Hellawell, & Hay (1987)

14. Reducing the effects of inaccuracy 32 original composites. 32 composites horizontally split below the eyes and misaligned. Direction of split counterbalanced. 32 new participants viewed 16 of each with each target represented once. Conditional hit rate

15. Split composites Original17.8% Split 24.1% F(1,30) = 5.39, p<.05 Disruption of inaccurate configurations? Multiple processing of parts?

16. Type or quantity of processing? 32 original composites. 32 split-morphed composites. 32 new participants viewed 16 of each with each target represented once. Conditional hit rate.

17. Split-morph composites Original 15.4% Split-morph24.6% F(1,30) = 20.87, p<.001 (Morph 32.4%) Disruption of an accurate configuration inhibits identification.

18. Composite naming

19. Conclusion Splitting facial composites produces a significant gain in identification rates. Requires just a simple image editor to make a significant impact on the successful detection of crime. The practical implication is clear, police forces should consider releasing split composites to the public, in order to boost the likelihood of an identification.

20. Comparison across experiments Mixed factor ANOVA Main effect of composite type (original or treated) F(1,93) = 55.4, p<.001. No effect of Experiment, p>.05. Significant interaction, F(2,93) = 4.00, p<.05. All treated composites were identified significantly better than the originals, p<.05. Identification of original composites did not differ across experiments (p>.05) Naming of split-morphs (24.6%) & split composites (24.1%) were comparable, p>.05, but significantly poorer than of morphed composites (32.4%) t(31) = 2.70, p<.05.

21. Student project – within subject design.