Drawing with AI -- Exploring Collaborative Inking Experiences Based on Mid-air Pointing and Reinforcement Learning
October 10, 2020 Β· Declared Dead Β· π arXiv.org
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Authors
Franziska Geiger, Michelle Martin, Monika Pichlmair, Ilhan Aslan, Hannes Ritschel, BjΓΆrn Bittner, Elisabeth AndrΓ©
arXiv ID
2010.05047
Category
cs.HC: Human-Computer Interaction
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Digitalization is changing the nature of tools and materials, which are used in artistic practices in professional and non-professional settings. For example, today it is common that even children express their ideas and explore their creativity by drawing on tablets as digital canvases. While there are many software-based tools, which resemble traditional tools, such as various forms of virtual brushes, erasers, etc. in contrast to traditional materials there is potential in augmenting software-based tools and digital canvases with artificial intelligence. Curious about how it would feel to interact with a digital canvas, which would be in contrast to a traditional canvas dynamic, responsive, and potentially able to continuously adapt to its user's input, we developed a drawing application and conducted a qualitative study with 14 users. In this paper, we describe details of our design process, which lead up to using a k-armed bandit as a simple form of reinforcement learning and a LeapMotion sensor to allow people from all walks of like, old and young to draw on pervasive displays, small and large, positioned near or far.
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