Colours and Faces

Tzu-Pei Grace ChenSidney Fels

Human Communication Technologies Lab

Presentation outline• Colours and face relations

• offer a good starting point to tackle face metric problem

• Results from second pilot tests

• Discussion

Role of the human face

Identity

Communication

Attractiveness

Challenge in face recognition

Is there a face metric system that can adequately quantify all

existing faces?

Why is it difficult in quantifying faces?

• Faces are transient

• We have sharp face recognition skills

• Infinite dimensions and acute recognition makes it hard

Previous work

• Face similarity metric– Eigenface [Turk and

Pentland]– Shape free face [Craw

et al and Bruce et al]

• Face attractiveness metric– Beauty mask

[Marquardt]

Why is colour metaphor a good starting point?

• Multi-dimensional

• Well-researched (many systems)

• Has less dimension than faces

• Good to model from a smaller example

Colour and face relations

• Colour-blindness vs. face-blindness

• Verbal over-shadowing effect

• Colour, emotion and facial expression.

• Colour vs. face opponent mechanism

• Primary colours and existence of primary faces

Colour blindness and face blindness

Normal Blind

Colour

Face

Opponent mechanism

Verbal foreshadowing

• Memory of both face and colours can be impaired if verbalized after studied

• For faces, this is due to a lack of words to describe the holistic properties

• Verbal descriptions limited to face features

• Perceptual ability surpass verbal ability• Same for colours

Plutchik’s model of emotions

Primary faces?

• DNA evidence• Localization of

mating habit

Second experiment

• Investigating two types of axes and two kinds of interface.

interface

axes

wheel

dynamic slider

T-S uncorrelated T-S correlated

Findings from second pilot test

• Subjects refine their match around the range of distance [1,2] from the target

subject 5 replicate 2 correlated wheel

02468

101214

0 1

1.41

42136

1.73

20508 2

2.23

6068

2.64

57513

2.82

84271

distance to target

nu

mb

er o

f ar

riva

ls

• The hump occurs most frequently with correlated sliders

Conclusion from pilot test

• For a small face space…

interface

axes

wheel

dynamic slider

T-S uncorrelated T-S correlated

Summary

•Colour metaphor seems like a good starting point to tackle face metric problem•Second pilot test- work in progress

–investigates additive and subtractive face system

The End