MAKING FACES:

ALLEN GRABO

MANIPULATING FACIAL CHARACTERISTICS USING FACEGEN AND PSYCHOMORPH

1. CREATING ARTIFICIAL FACES

A Data-Driven Approach

Torodov et al, 2010 (link) were the first to develop a computational model of social judgements from faces

Using a program called FaceGen they created a database of faces designed to be maximally distinct from one another

These were rated by thousands of participants to provide external validity

Transformations along all other dimensions are controlled for attractiveness

. . .

FACEGEN EXAMPLES: 25 ‘INDIVIDUALS’ MORPHED ALONG 7 DIMENSIONS

[link to originals]

FACEGEN EXAMPLES:‘INDIVIDUALS’ AND TRAITS

Competence

Dominance

Extroversion

Trustworthiness

FACEGEN EXAMPLES:‘INDIVIDUALS’ AND TRAITS

Attractiveness (Neutral, Low, High)

Extroversion (Neutral, Low, High)

FACEGEN EXAMPLES:‘INDIVIDUALS’ AND TRAITS

Competence (Neutral, Low, High)

Dominance (Neutral, Low, High)

II. PSYCHOMORPH

The problem with artificial faces….

Computational models can create “maximally distinct” faces on each dimension

However, the faces are clearly not real

To overcome this limitation, we use a set of algorithms which have been under development for nearly 20 years (link)

Psychomorph (now called Webmorph) allows us to use these prototypes to transform real faces along the dimensions identified by Todorov

UntrustworthyTrustworthy

SO LET’S START WITH AN “AVERAGE” FACE

SO LET’S START WITH AN “AVERAGE” FACE

SO LET’S START WITH AN “AVERAGE” FACE

SIDE-BY-SIDE:EFFECT OF 70% FEMININE / MASCULINE TRANSFORM

VIDEO EXAMPLE OF MASCULINE – FEMININE TRANSFORM

SIDE-BY-SIDE:EFFECT OF 70% TRUSTWORTHINESS TRANSFORM

VIDEO EXAMPLE OF TRUSTWORTHY TRANSFORM

SIDE-BY-SIDE:EFFECT OF 70% DOMINANCE TRANSFORM

VIDEO EXAMPLE OF DOMINANCE TRANSFORM

MORPHING FROM ONE FACE TO ANOTHER

MULTIPLE MORPHS