Autocomplete Repetitive Stroking with Image Guidance

Yilan Chen, Kin Chung Kwan, Li-Yi Wei, Hongbo Fu

SIGGRAPH Asia 2021 Technical Communication


Image-guided drawing can compensate for the lack of skills but often requires a significant number of repetitive strokes to create textures. Existing automatic stroke synthesis methods are usually limited to predefined styles or require indirect manipulation that may break the spontaneous flow of drawing. We present a method to autocomplete repetitive short strokes during users' normal drawing process. Users can draw over a reference image as usual. At the same time, our system silently analyzes the input strokes and the reference to infer strokes that follow users' input style when certain repetition is detected. Our key idea is to jointly analyze image regions and operation history for detecting and predicting repetitions. The proposed system can reduce tedious repetitive inputs while being fully under user control.

Available information

paper (arXiv) video (youtube)