2023

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https://diglib.eg.org/handle/10.2312/2633352

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Browsing 2023 by Subject "Curve fitting"

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    Processing Freehand Vector Sketches
    (University of British Columbia, 2023-06-22) Liu, Chenxi
    Freehand sketching is a fast and intuitive way for artists to communicate visual ideas, and is often the first step of creating visual content, ranging from industrial design to cartoon production. As drawing tablets and touch displays become increasingly common among professionals, a growing number of sketches are created and stored digitally in vector graphics format. This trend motivates a series of downstream sketch-based applications, performing tasks including drawing colorization, 3D model creation, editing, and posing. Even when stored digitally in vector format, hand-drawn sketches, often containing overdrawn strokes and inaccurate junctions, are different from the clean vector sketches required by these applications, which results in tedious and time-consuming manual cleanup tasks. In this thesis, we analyze the human perceptual cues that influence these two tasks: grouping overdrawn strokes that depict a single intended curve and connecting unintended gaps between strokes. Guided by these cues, we develop three methods for these two tasks. We first introduce StrokeAggregator, a method that automatically groups strokes in the input vector sketch and then replaces each group by the best corresponding fitting curve—a procedure we call sketch consolidation. We then present a method that detects and resolves unintended gaps in a consolidated vector line drawing using learned local classifiers and global cues. Finally, we propose StripMaker, a consolidation method that jointly considers local perception cues from the first method and connectivities detected by the second method. We further integrate observations about temporal and contextual information present in drawing, resulting in a method with superior consolidation performance and potential for better user interactivity. Together, this work identifies important factors in humans’ perception of freehand sketches and provides automatic tools that narrow the gap between the raw freehand vector sketches directly created by artists and the requirements of downstream computational applications.