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“What I See Is What You Get” Explorations of Live Artwork Generation, Artificial Intelligence, and Human Interaction in a Pedagogical Environment

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Interactivity, Game Creation, Design, Learning, and Innovation (ArtsIT 2019, DLI 2019)

Abstract

In this paper we review the overall process for the design, development, and deployment of “What I See Is What You Get”, an experiential installation that creates live interactive visuals, by analyzing human facial expressions and behaviors, accompanied by text generated using Machine Learning algorithms trained on the art collection of The J. Paul Getty Museum in Los Angeles. The project is developed by students and faculty in an academic environment and exhibited at the Getty Museum. We also study the pedagogical process implemented to address the curriculum’s learning outcomes in an “applied” environment while designing a contemporary new media art piece. Special attention is paid to the level and quality of the interaction between users and the piece, demonstrating how advances in technology and computing such as Deep Learning and Natural Language Processing can contribute to deeper connections and new layers of interactivity.

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References

  1. Tribe, M., Jana, R., Grosenick, U.: New Media Art (Taschen Basic Art). Taschen America, LLC (2006)

    Google Scholar 

  2. Krueger, M.W.: Responsive environments. In: AFIPS 1977 Proceedings of the June 13–16, 1977, National Computer Conference, pp. 423–433. Dallas, Texas (1977)

    Google Scholar 

  3. Krauth AK: Using handmade controllers for interactive projection mapping. In: Proceedings of the 23rd ACM International Conference on Multimedia - MM 2015, pp 717–719. ACM Press, Brisbane, Australia (2015)

    Google Scholar 

  4. Manovich, L.: Automating aesthetics: artificial intelligence and image culture. In: Flash Art International, no. 316 (2017). https://flash---art.com/issue/316-september-october-2017/. Accessed 14 Aug 2019

  5. OpenCV. https://opencv.org/. Accessed 10 Aug 2019

  6. PyCharm: The Python IDE for Professional Developers by JetBrains. https://www.jetbrains.com/pycharm/. Accessed 10 Aug 2019

  7. Derivative TouchDesigner. https://www.derivative.ca/. Accessed 10 Aug 2019

  8. KINECTONE. https://developer.microsoft.com/en-us/windows/kinect. Accessed 10 Aug 2019

  9. Structure Sensor-3D scanning, augmented reality, and more for mobile devices. https://structure.io/. Accessed 10 Aug 2019

  10. Viola, P., Jones, M.J.: Robust real-time face detection. Int. J. Comput. Vis. 57(2), 137–154 (2004). Kluwer Academic Publishers Norwell, MA

    Google Scholar 

  11. Teixeira Lopes, A., de Aguiar, E., Oliveira-Santos, T.: A facial expression recognition system using convolutional networks. In: Conference on Graphics, Patterns and Images (SIBGRAPI), 28th Conference, Salvador, Brazil, pp. 273–280 (2015)

    Google Scholar 

  12. Rothe, R., Timofte, R., Gool, L.V.: DEX: deep expectation of apparent age from a single image. In: 2015 IEEE International Conference on Computer Vision Workshop (ICCVW), pp. 252–257 (2015)

    Google Scholar 

  13. Keras Documentation. https://keras.io/. Accessed 10 Aug 2019

  14. TensorFlow. https://www.tensorflow.org/. Accessed 10 Aug 2019

  15. Radford, A., Wu, J., Child, R., Luan, D., Amode, D., Sutskever, I.: Language models are unsupervised multitask learners. In: Technical report, OpenAI (2019). https://openai.com/blog/better-language-models/. Accessed 14 Aug 2019

  16. Google Colaboratory. https://github.com/ak9250/gpt-2-colab. Accessed 10 Oct 2019

  17. Python Data Analysis Library. https://pandas.pydata.org/. Accessed 18 Oct 2019

  18. Woolf, M.: Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code: minimaxir/textgenrnn (2015). https://github.com/minimaxir/textgenrn

  19. Kaggle Facial Expression Recognition Challenge. https://www.kaggle.com/c/challenges-in-representation-learning-facial-expression-recognition-challenge/. Accessed 18 Oct 2019

  20. ACS-Woodbury Github Repository. https://github.com/ACS-Woodbury/WISIWYG.git. Accessed 19 Oct 2019

  21. Parkhi, O.M., Vedaldi, A., Zisserman, A.: Deep face recognition. In: British Machine Vision Conference (2015). http://www.robots.ox.ac.uk/~vgg/publications/2015/Parkhi15/parkhi15.pdf

  22. Large Scale Visual Recognition Challenge 2014. http://image-net.org/challenges/LSVRC/2014/. Accessed 18 Oct 2019

  23. IMDB-WIKI Dataset - 500 k+ face images with age and gender labels. https://data.vision.ee.ethz.ch/cvl/rrothe/imdb-wiki/. Accessed 10 Aug 2019

  24. Apparent Age and Gender Prediction in Keras. https://sefiks.com/2019/02/13/apparent-age-and-gender-prediction-in-keras/

  25. Connor, A.M., Sosa, R.: The A-Z of creative technologies. EAI Endorsed Trans. Creative Technol. 5, 1–2 (2018)

    Google Scholar 

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Correspondence to Ana Herruzo .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Herruzo, A., Pashenkov, N. (2020). “What I See Is What You Get” Explorations of Live Artwork Generation, Artificial Intelligence, and Human Interaction in a Pedagogical Environment. In: Brooks, A., Brooks, E. (eds) Interactivity, Game Creation, Design, Learning, and Innovation. ArtsIT DLI 2019 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 328. Springer, Cham. https://doi.org/10.1007/978-3-030-53294-9_23

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  • DOI: https://doi.org/10.1007/978-3-030-53294-9_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-53293-2

  • Online ISBN: 978-3-030-53294-9

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