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StrokeStyles SIGGRAPH 2022 presentation

Presentation for the paper StrokeStyles: Stroke-based Segmentation and Stylization of Fonts Daniel Berio, Frederic Fol Leymarie, Paul Asente, Jose Echevarria https://dl.acm.org/doi/10.1145/3505246 Abstract: We develop a method to automatically segment a font’s glyphs into a set of overlapping and intersecting strokes with the aim of generating artistic stylizations. The segmentation method relies on a geometric analysis of the glyph’s outline, its interior, and the surrounding areas and is grounded in perceptually informed principles and measures. Our method does not require training data or templates and applies to glyphs in a large variety of input languages, writing systems, and styles. It uses the medial axis, curvilinear shape features that specify convex and concave outline parts, links that connect concavities, and seven junction types. We show that the resulting decomposition in strokes can be used to create variations, stylizations, and animations in different artistic or design-oriented styles while remaining recognizably similar to the input font.