GENERATING AFFECTIVE CHARACTERS
FOR ASSISTIVE APPLICATIONS
Diana Arellano, Isaac Lera, Javier Varona and Francisco J. Perales
Computer Graphics, Vision and Artificial Intelligence Group
Universitat de les Illes Balears (UIB).
Palma de Mallorca, Spain
August 2009
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
AGENDA
1.- Motivation – What are we looking for?
2.- Objective – What did we do?
3.- Breaking into pieces
4.- Results
5.- Applications
6.- Conclusions
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
1.-What were
we looking for?
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
1.- What were we looking for?
Individuals
Unique
Different
Distinguishable
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
1.- What were we looking for?
Realism
ORIGINAL PICTURE
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
RENDER
1.- What were we looking for?
More Humans
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
1.- What were we looking for?
Characters that:
• Have personality
• Feel emotions
• Manifest emotional states
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
2.-What was the
objective?
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
2.- Objective
World
represented by
generates
Emotions
Semantic
Knowdlege
produce
influenced
by
Personality
Emotional
States
manifested
by
Facial
Expressions
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
2.- Objective
We explore:
• The role of new technologies and theories that explore
human affect.
• How they can be used by persons in everyday life.
• The creation of virtual characters for specific applications
developed for physically, or mentally, disable people.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.-Breaking into
pieces …
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
World
What surrounds and occurs to the character
= EVENTS
Action
Place
People
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
Time
3.- Breaking into pieces …
World
What is inside the character
Goals
Agent
Admiration
Preferences
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
World
represented by
Semantic
Knowdlege
ONTOLOGIES
?
?
?
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
ONTOLOGY:
Formal representation of a set of concepts within a
domain and the relationships between those concepts.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
World
represented by
generates
Emotions
Semantic
Knowdlege
influenced
by
Personality
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
Personality
YEARS
Five Factor Model
(OCEAN)
- Opennes to Experience
- Conscientiousness
- Extraversion
- Agreeableness
- Neuroticism
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces …
Emotions
MINUTES
Ekman + OCC Model
- Ekman: Happiness, Sadness, Disgust, Anger, Fear, Surprise.
- OCC Model (Ortony, Clore
and Collins):
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
World
represented by
generates
Emotions
Semantic
Knowdlege
produce
influenced
by
Personality
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
Emotional
States
3.- Breaking into pieces …
PAD Space: Pleasure-Arousal-Dominance
(+P+A+D) Exuberant
Proposed by Albert Mehrabian
(-P-A-D) Bored
+D
(+P-A+D) Relaxed
-A
(-P+A-D) Anxious
-P
(+P+A-D) Dependent
+P
(-P-A+D) Disdainful
+A
(+P-A-D) Docile
(-P+A+D) Hostile
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
How did we do it?
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
ES: Emotional State
ES
Intensity of Emotional State
-A
-P
,if
Slightly
+P
+A
PAD Space
-D
Moderate
Highly
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
DES
-A
-P
+P
+A
PAD Space
-D
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
DES
Ei: Emotions
E1
E2
-A
-P
E3
+P
+A
PAD Space
-D
Emotion
P
A
D
Octant
Anger
-0.51
0.59
0.25
Hostile
Disgust
-0.4
-0.2
0.1
Disdainful
Disappoint.
-0.3
-0.4
-0.4
Sadness
Sadness
-0.4
-0.2
-0.5
Sadness
Fear
-0.64
0.6
-0.43
Anxious
Relief
0.2
-0.3
0.4
Relaxed
…
…
…
…
…
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
DES
Ei: Emotions
E1
E2
EC
-P
-A
EC: Center of Mass(Ei)
E3
+P
+A
PAD Space
EC: Emotional Center
-D
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
DES
E1
ES
E2
EC
-P
Ei: Emotions
E1
-A
EC: Emotional Center
E2
At time 0 in the process:
E3
E3
+P
+A
PAD Space
ES: Emotional State
ES: displacement of DES due to EC
-D
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
E1
ES(t)
ES(t+1)
ES
-P
Ei: Emotions
E1
E2
EC
-A
EC: Emotional Center
E2
At time ‘t+1’:
ES(t): Actual Emotional State (en ‘t’)
E3
ES(t+1): New Emotional State (en ‘t+1’)
+P
+A
PAD Space
-D
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Affective Model
Implementing an Affective Model
+D
DES: Default Emotional State
DES
Ei: Emotions
E1
ESdec
ESdec: Decayed Emotional State
-A
-P EE(t+1)
E2
Decay:
E3
ESdec: Center of Mass(DES, EE(t+1))
+P
+A
PAD Space
-D
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces …
World
represented by
generates
Emotions
Semantic
Knowdlege
produce
influenced
by
Personality
Emotional
States
manifested
by
Facial
Expressions
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Emotional State
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
Emotions
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Universal
Happiness, Sadness,
Anger, Disgust, Fear,
Surprise
Emotions
Intermediate
EMOTIONS & MACHINES Workshop
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Hate, Love, Pity,
Disappointment …
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Expressions of Universal Emotions
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Expressions of Intermediate Emotions
Universal
Intermediate
+
=
Universal
Intermediate
≈
Universal
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
GENERATION OF
EXPRESSIONS
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
1. MPEG-4 Standard:
FDPs: Facial Definitions Parameters
4.1
Right corner of left eyebrow
4.2
Left corner of right eyebrow
4.3
Uppermost point of the left eyebrow
4.4
Uppermost point of the right eyebrow
4.5
Left corner of left eyebrow
…
…
Face
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
1. MPEG-4 Standard:
3
Open_jaw
4
lower t midlip
5
raise b midlip
6
stretch l cornerlip
7
stretch r cornerlip
…
…
FAPs: Facial Animation Parameters
FAP 5 = 500
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
2. Whissell
Wheel
Activation (
)
Evaluation (
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
)
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Case 1: Two universal emotions involved
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Case 1: Two universal emotions involved
1.- The range of a FAP is:
FAP 5: raise bottom midlip
FAP 5 = 0
500
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Case 1: Two universal emotions involved
2.- Activation values according to Whissell Wheel:
3.- Angular distance between emotions:
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Surprise
Joy
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
=
+
Happiness
Surprise
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
Admiration
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
+
Sadness
=
Fear
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
Pity
3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
Case 2: One universal emotion involved
a) The range of
is subrange of the universal emotion.
EMOTIONS & MACHINES Workshop
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3.- Breaking into pieces … Generation of Facial Expressions
Visualizing Emotional States:
≈
Happiness
Liking
EMOTIONS & MACHINES Workshop
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4.-Which were
the results?
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
Objective: Demonstrate the coherence of the affective results given a
definition of the character and their environment.
I. Story with 5 relevant EVENTS:
1.- Breakfast oats in the kitchen.
2.- Getting email with rejection for conference
3.- Arguing with best friend
4.- Reconcilitation with best friend
5.- Dinner with flatmates at home
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
II. 2 different PERSONALITIES were defined:
Personality 1 (P1): Very NEUROTIC
Very UNFRIENDLY
(N = 0.99)
(A = - 0.99).
Personality 2 (P2): Very EXTROVERTED (E = 0.99)
Very FRIENDLY
EMOTIONS & MACHINES Workshop
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(A = 0.99)
4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
III. Event:
Dinner at 21:00 with flatmates at home
what
when
who
where
Configurations: describe PREFERENCES, GOALS and ADMIRATION for other AGENTS.
Configuration 1 (C1):
Configuration 2 (C2):
(a) Living room at home: Good (0.7), Indifferent (0.3)
(b) 21:00: Good (0.9), Indifferent (0.1)
(c) Flatmates: Positive (0.8), Indifferent (0.2)
(d) Have dinner with flatmates: Goal: Des(0.7)
Satisfactory (0.7)
Indifferent (0.2)
Not Satisfactory (0.1)
(a) Living room at home: Bad (0.7), Indifferent (0.3)
(b) 21:00: Bad (0.9), Indifferent (0.1)
(c) Flatmates: Negative (0.8), Indifferent (0.2)
(d) Have dinner with flatmates: Not Satisfactory (0.7)
Indifferent (0.2)
Satisfactory (0.1)
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
IV. Triggered Emotions: using EMOTIONAL CATEGORIZATION and FUZZY RULES.
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
V. Triggered Emotional States:
P1: NEUROTIC and UNFRIENDLY
C1: Positive feelings
P2: EXTROVERTED and FRIENDLY
C2: Negative feeling
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Facial Expressions for Emotional States:
Moderate Exuberant
Slightly Disdainful
Fully Exuberant
Slightly Exuberant.
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
A = -0.99 (hard-headed, skeptical, competitive, proud, good to be leader)
N = 0.99 (negative reactions, prone to worry, anxiety)
Disdainful
(Default Emotional State)
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Evento 1: Breakfast oats in the kitchen (She hates oats)
Hostile 0.3
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Decay:
Disdainful 0.42
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Event 2: She loves researching. Got a rejection from a very important
conference.
Bored 0.26
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Event 3: She argues with her best friend and she is really concerned
Bored 0.77
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Decay:
Bored 0.61
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Event 4: She makes up with her best friend.
Relaxed 0.08
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
Event 5: Dinner with friends in her flat.
Exuberant 0.77
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VI. Another example: Set P1-C1
All Events with Configuration 1, felt with Personality 1
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VII. Experimentation:
•Evaluation set: 20 animations generated using the MPEG-4 standard.
Each animation shows the transition between previous emotional state to the
actual emotional state produced by its event categorized as P1-C1 or P2-C1,
with P1-C2 or P2-C2.
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VII. Experimentation:
•
Participants: 21 persons (4 women and 17 men) between 20 and 41 years
old, different academic backgrounds.
•
Procedure: show 3 animations per event: the correct one and two incorrect
ones, randomly ordered.
1) Read the event, the personality, and the emotional state of the
character after the occurrence of the event.
2) Observed the three animations, twice.
3) Marked in the questionary the animation (A1, A2, A3) they considered
more appropriate to the situation.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
Event: Dinner with friends in her flat (she does not like having guests).
•P1: Neurotic and Unfriendly.
Disdainful -> Disgust = 0.115.
Correct.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
VIII. Results:
Percentage of persons that correctly associate “situation - emotional state facial expression”.
P1-C1
P2-C1
P1-C2
P2-C2
1.- Breakfast oats in the kitchen (%)
72
29
62
95
2.- Getting email with rejection for conference (%)
71
52
71
76
3.- Arguing with best friend (%)
81
81
48
67
4.- Reconcilitation with best friend (%)
76
85
76
85
5.- Dinner with flatmates at home (%)
85
29
95
62
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Computational Model Evaluation: Semantic and Affective Model
IX. Conclusion:
- More EXPRESSIVENESS on faces with strong personalities.
- Having 3 variables in consideration (event, personality and emotional
state) results too confusing for people to evaluate the correlation among
them.
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Subjetive Evaluation: Survey applied to 75 Computer Science
students between 18 and 40 years old.
1.- Which basic emotion do you recognize in the expression?
 86% of the expressions CORRECTLY recognized.
X Fear and surprise were confused. Disgust was not easily recognized.
Easily Recognized
Hardly Recognized
Happiness
(93 %)
Reproach
(54 %)
Sadness
(87 %)
Fear
(52 %)
Admiration
(86 %)
Pity
(52 %)
Anger
(84 %)
Disappointment
(38 %)
Satisfaction (84 %)
Neutral
(80 %)
Surprise
(70 %)
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
2.- Which emotional state do you recognize in the expression?
(IMPORTANT: They were grouped by Dominance:
Anxious-Hostile,
Bored-Disdainful,
Exuberant-Dependent,
Relaxed-Docile)
 73% of the expressions CORRECTLY associated.
 Surprise was associated with Anxious-Hostile state.
X Positive emotions were easier to associate. Negative were not.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
4.- Evaluation and Results
3.- Which emotional state do you recognize in the video?
(IMPORTANT: They were grouped by Dominance:
Anxious-Hostile,
Bored-Disdainful,
Exuberant-Dependent,
Relaxed-Docile)
Emotion
Recognized Emotional State
Sadness
Bored-Disdainful
Happiness
Exuberant-Dependent 88 %
Anger
Anxious-Hostile
85 %
Disgust
Bored-Disdainful
61 %
Fear
Exuberant-Dependent 57 %
Surprise
Exuberant-Dependent 53 %
93 %
EMOTIONS & MACHINES Workshop
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4.- Evaluation and Results
Objective Evaluation: Automatic recognizer of facial expressions
developed in collaboration with GIGA team from the University of
Zaragoza (INEVAI 3d project).
 82% of the expressions CORRECTLY recognized.
 Comparing with subjective evaluation results were similar most of
the times.
X Hope, pity and reproach = Aversion.
X Fear confused with surprise.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
5.-What is this
useful for?
EMOTIONS & MACHINES Workshop
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5.- Applications
1.- Tangible Interfaces for disable and elderly users:
We propose the development of a tangible avatar in charge of the
elderly’s assistance, with tele-assistance functionalities in chronic
cases.
 Reaction capability, facing events and environment changes.
 Planning capability and decision making, to carry out the tasks according
to one or more objectives.
 Efficiency in decision making and in carrying out tasks.
 Interaction capability and communication with other agents.
 Capability to adapt to other environments.
EMOTIONS & MACHINES Workshop
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5.- Applications
1.- Tangible Interfaces for disable and elderly users:
Advantages:
 Reduces new technologies rejection.
 Facilitates the use of the application by an elderly person. Feeling that
someone else is in charge of the system.
 Increments empathy with situations and feeling of the user.
Disadvantages:
X Too much realism = Uncanny valley.
X Exhaustive evaluation of the visual appearance and behavior of the
avatar before implementing it in a real application.
EMOTIONS & MACHINES Workshop
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5.- Applications
1.- Tangible Interfaces for disable and elderly users:
EMOTIONS & MACHINES Workshop
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5.- Applications
2.- Virtual trainer for developing social abilities:
We propose the development of a virtual character that facilitates
the task of helping people to express, or suppress, the expression
of their emotions.
Advantages:
 Virtual model used as a base to show how the face is moved and
changed when expressing certain emotions.
 Framework with a set of daily events to train the patient and help him to
express the felt emotion.
 Improve communication abilities.
 Assistive tool in therapy to increase emotion recognition with people with
autism or Asperger syndrome.
EMOTIONS & MACHINES Workshop
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5.- Applications
2.- Virtual trainer for developing social abilities:
Disadvantages:
X People with severe communication and language problems may not be
able to recognize any emotion at all.
X Exhaustive research on the appearance of the avatar to make it usable
by the patient.
X Learning curve can be extremely slow.
EMOTIONS & MACHINES Workshop
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6.-Which are the
conclusions?
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
6.- Conclusions
 Coherent elicitation and transition of emotional states according
to certain personality traits and events.
 Generation of recognizable intermediate emotions using basic
emotions.
 Satisfactory recognition of emotional states in facial
expressions. Especially those in videos!!!
 Affective avatars can be of great use as therapy for people with
communication problems. MUSIC can help in the engagement of
the user with the application.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
6.- Conclusions
+ Lack of context, voice, and movement (static images) make
harder the recognition.
+ Positive emotions are hard to differentiate among them.
Problem: “Duchenne Smile”.
+ Expressions for extroverted characters need to be more
exaggerated.
+ A refinement of evaluation of the computational model is needed.
Less variables to take into account, and let subject assess the
resulting emotional value.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
What’s for the
future?
Current and future work
 Head movement, eye movement, blinking = REALISM!
 Use of Geneva Wheel to validate emotion recognition.
 Implementation of our own developed ontology that defines the
character and their environment, through an Affective Avatar/ Virtual
Tutor.
 Application of the computational model in a tool that helps to the
communication skills improvement of people with autism or Asperger
syndrome.
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
GENERATING AFFECTIVE CHARACTERS
FOR ASSISTIVE APPLICATIONS
THANK YOU
QUESTIONS??
Diana Arellano, Isaac Lera, Javier Varona and Francisco J. Perales
Unitat de Gràfics i Visió per Ordinador, i Intel·ligència Artificial
Universitat de les Illes Balears (UIB).
Palma de Mallorca, Spain
August, 2009
EMOTIONS & MACHINES Workshop
Geneva, Switzerland.
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