A Creative Artificial Intelligence System to Investigate User Experience, Affect, Emotion and Creativity

Is it possible using photographs as source (e.g., selfies of users) to affect and enhance mood, emotion and creativity by creating AI based “digital painters” that can create art painting output that is deemed to convey a certain mood from any source photograph (user face portraits, dancers in moment)? The goal of this research is to use our Creative Artificial Intelligence System (CAIS) along with our cognitive based painting algorithms (DiPaola 2013) together with additional art analysis tools (i.e., texture and palette synthesis) to parameterize a generative artistic painting process based on mood and emotion. We discuss our methods and begin to validate the work by performing two intertwined user studies that appear to support that viewers of the generated art from our CAIS agree to a high degree on a specific mood the output conveys from our 4 emotional spaces regardless of the source material: abstract, fugitive or their self portrait. This points to the conclusion that our CAIS system can automatically generate unique artworks or “aesthetic visualization” that deemed creative and have emotional qualities, which has benefits and repeatability in many interactive fields. This work has User Experience (UX) applications in computational creativity, affective aesthetic visualization, experiential learning (of art), performance visualization (dancing), and health well-being.

Content

Author and article information

Contributors

Sara Salevati

Steve DiPaola

Conference

Publication date: July 2015

Publication date (Print): July 2015

Pages: 140-147

Affiliations

[0001]Simon Fraser University

888 University Dr. Burnaby BC

Canada V5A1S6

Article

DOI: 10.14236/ewic/eva2015.13

SO-VID: 35bff5d7-0a85-46f5-94c7-a4c4bf6b565d

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: Electronic Visualisation and the Arts (EVA 2015)

Conference acronym: EVA

Conference number:

Conference location: London, UK

Conference date: 7 & 9 July 2015

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Electronic Visualisation and the Arts

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/eva2015.13

Self URI (journal page): https://ewic.bcs.org/

REFERENCES

M. M BradleyP. J Lang 2000 Measuring emotion: Behavior, feeling, and physiology R. D LaneL Nadel Cognitive Neuroscience of Emotionp242 276 Oxford University Press New York
M. M BradleyM CodispotiB. N CuthbertP. J Lang 2001 Emotion and Motivation I: Defensive and Appetitive Reactions in Picture Processing Emotion 1 3 276 298
J Deeth 2013 Engaging Strangeness in the Art Museum: an audience development strategy Museum and Society 10 1 1 14
S DiPaolaS Salevati 2014 Using a Creative Evolutionary System for Experiencing the Art of Futurism International Conference on Electronic Imaging & the Visual Arts EVA 2014 Florence, Italyp88 93
S DiPaolaS Salevati 2014 AI based analysis and generation of aesthetic interactive visualizations of art styles and human movement International Symposium on Computational Aesthetics in Graphics, Visualization, & Imaging Poster and Demo Vancouver, BC, Canada
S DiPaolaR McCaigK CarsonS SalevatiN Sorenson 2013 Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition International Conference on Computational Creativity (ICCC, 2013) Sydney, Australiap40 47
S DiPaolaA Smith 2013 Interactively Exploring Picasso’s Multi-dimensional Creative Process in Producing Guernica Electronic Visualisation and the Arts (EVA 2013) London, UKp25 31 British Computer Society London
S DiPaolaC RiebeJ Enns 2010 Rembrandt’s Textural Agency: A Shared Perspective in Visual Art and Science Leonardo 43 3 145 151
S DiPaola 2009 Exploring a Parameterized Portrait Painting Space International Journal of Art and Technology 2 1–2 82 93
S DiPaola 2007 A Knowledge Based Approach to Modeling Portrait Painting Methodology Electronic Visualisation and the Arts (EVA 2007) London, UK. British Computer Society London
S DiPaola 2005 Evolving Creative Portrait Painter Programs Using Darwinian Techniques with an Automatic Fitness Function Electronic Visualisation and the Arts (EVA 2005) London, UK British Computer Society, London 10 pages
P FagerbergA StåhlK Höök 2003 Designing gestures for affective input: an analysis of shape, effort and valence Mobile Ubiquitous and Multimedia (MUM 2003) Norrköping Sweden
K GibbsM SaniJ Thompson 2000 Lifelong Learning in Museums Ferrara, Italy EDISAI
C. R JohnsonE HendriksI. J BerezhnoyE BrevdoS. M HughesI DaubechiesJ LiE PostmaJ. Z Wang 2008 Image processing for artist identification: computerized analysis of Vincent van Gogh’s painting brushstrokes IEEE Signal Processing Magazine Special Issue on Visual Cultural Heritage 25 4 37 48
D JoshiR DattaQ. T Luong 2011 Aesthetics and Emotions in Images: A Computational Perspective IEEE Signal Processing Magazine 28 5 94 115
J.A Russell 1980 A circumplex model of affect Journal of Personality and Social Psychology 39 6 1161 1178
J. A RussellA WeissG. A Mendelsohn 1989 Affect Grid: A Single-Item Scale of Pleasure and Arousal Journal of Personality and Social Psychology 57 3 493 502
S SalevatiS DiPaola 2015 Enhancing Viewer’s Emotional Connections to the Traditional Art Creative Process via an AI Interactive System International Conference on Electronic Imaging & the Visual Arts (EVA 2015) Florence, Italy
P SundströmA StahlK Höök 2005 eMoto: affectively involving both body and mind Proc. of CHI EA 2005 2005–2008
P SundströmA StåhlK Höök 2005 eMoto – A user-centred approach to affective interaction Proceedings of ACII05 Beijing, China. Lecture Notes in Computer Science Springer

Comments

Comment on this article

[1] M. M BradleyP. J Lang 2000 Measuring emotion: Behavior, feeling, and physiology R. D LaneL Nadel Cognitive Neuroscience of Emotionp242 276 Oxford University Press New York

[2] M. M BradleyM CodispotiB. N CuthbertP. J Lang 2001 Emotion and Motivation I: Defensive and Appetitive Reactions in Picture Processing Emotion 1 3 276 298

[3] J Deeth 2013 Engaging Strangeness in the Art Museum: an audience development strategy Museum and Society 10 1 1 14

[4] S DiPaolaS Salevati 2014 Using a Creative Evolutionary System for Experiencing the Art of Futurism International Conference on Electronic Imaging & the Visual Arts EVA 2014 Florence, Italyp88 93

[5] S DiPaolaS Salevati 2014 AI based analysis and generation of aesthetic interactive visualizations of art styles and human movement International Symposium on Computational Aesthetics in Graphics, Visualization, & Imaging Poster and Demo Vancouver, BC, Canada

[6] S DiPaolaR McCaigK CarsonS SalevatiN Sorenson 2013 Adaptation of an Autonomous Creative Evolutionary System for Real-World Design Application Based on Creative Cognition International Conference on Computational Creativity (ICCC, 2013) Sydney, Australiap40 47

[7] S DiPaolaA Smith 2013 Interactively Exploring Picasso’s Multi-dimensional Creative Process in Producing Guernica Electronic Visualisation and the Arts (EVA 2013) London, UKp25 31 British Computer Society London

[8] S DiPaolaC RiebeJ Enns 2010 Rembrandt’s Textural Agency: A Shared Perspective in Visual Art and Science Leonardo 43 3 145 151

[9] S DiPaola 2009 Exploring a Parameterized Portrait Painting Space International Journal of Art and Technology 2 1–2 82 93

[10] S DiPaola 2007 A Knowledge Based Approach to Modeling Portrait Painting Methodology Electronic Visualisation and the Arts (EVA 2007) London, UK. British Computer Society London

[11] S DiPaola 2005 Evolving Creative Portrait Painter Programs Using Darwinian Techniques with an Automatic Fitness Function Electronic Visualisation and the Arts (EVA 2005) London, UK British Computer Society, London 10 pages

[12] P FagerbergA StåhlK Höök 2003 Designing gestures for affective input: an analysis of shape, effort and valence Mobile Ubiquitous and Multimedia (MUM 2003) Norrköping Sweden

[13] K GibbsM SaniJ Thompson 2000 Lifelong Learning in Museums Ferrara, Italy EDISAI

[14] C. R JohnsonE HendriksI. J BerezhnoyE BrevdoS. M HughesI DaubechiesJ LiE PostmaJ. Z Wang 2008 Image processing for artist identification: computerized analysis of Vincent van Gogh’s painting brushstrokes IEEE Signal Processing Magazine Special Issue on Visual Cultural Heritage 25 4 37 48

[15] D JoshiR DattaQ. T Luong 2011 Aesthetics and Emotions in Images: A Computational Perspective IEEE Signal Processing Magazine 28 5 94 115

[16] J.A Russell 1980 A circumplex model of affect Journal of Personality and Social Psychology 39 6 1161 1178

[17] J. A RussellA WeissG. A Mendelsohn 1989 Affect Grid: A Single-Item Scale of Pleasure and Arousal Journal of Personality and Social Psychology 57 3 493 502

[18] S SalevatiS DiPaola 2015 Enhancing Viewer’s Emotional Connections to the Traditional Art Creative Process via an AI Interactive System International Conference on Electronic Imaging & the Visual Arts (EVA 2015) Florence, Italy

[19] P SundströmA StahlK Höök 2005 eMoto: affectively involving both body and mind Proc. of CHI EA 2005 2005–2008

[20] P SundströmA StåhlK Höök 2005 eMoto – A user-centred approach to affective interaction Proceedings of ACII05 Beijing, China. Lecture Notes in Computer Science Springer

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