Automating the Intentional Encoding of Human-Designable Markers

Generative AI (Text, Image, Music, Video)Graphic Design & Typography ToolsProduct DesignersVisual Artists & Designers

Recent work established that it is possible for human artists to encode information into hand-drawn markers, but it is difficult to do when simultaneously maintaining aesthetic quality. We present two methods for relieving the mental burden associated with encoding, while allowing an artist to draw as freely as possible. A 'Helper Overlay' guides the artist with real-time feedback indicating where visual features should be added or removed, and an 'Autocomplete Tool' directly adds necessary features to the drawing for the artist to touch up. Both methods are enabled by a two-part algorithm that uses a tree-search for finding 'major' changes and a dynamic programming method for finding the minimum number of 'minor' changes. A 24-person study demonstrates that a majority of participants prefer both tools over previous methods of manual encoding, with the Helper Overlay being the more popular of the two.

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https://hci.top/en/papers/chi/6808/2019

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Source
CHI
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Year
2019
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3 authors
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Subtopics
Generative AI (Text, Image, Music, Video), Graphic Design & Typography Tools
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Professions
Product Designers, Visual Artists & Designers
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Abstract only
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