Guțan, OlgaHegde, ShreyaBerumen, Erick JimenezBessmeltsev, MikhailChien, EdwardMemari, PooranSolomon, Justin2023-06-302023-06-3020231467-8659https://doi.org/10.1111/cgf.14901https://diglib.eg.org:443/handle/10.1111/cgf14901State-of-the-art methods for line drawing vectorization rely on generated frame fields for robust direction disambiguation, with each of the two axes aligning to different intersecting curve tangents around junctions. However, a common source of topological error for such methods are frame field singularities. To remedy this, we introduce the first frame field optimization framework guaranteed to produce singularity-free fields aligned to a line drawing. We first perform a convex solve for a roughly-aligned orthogonal frame field (cross field), and then comb away its internal singularities with an optimal transport–based matching. The resulting topology of the field is strictly maintained with the machinery of discrete trivial connections in a final, non-convex optimization that allows non-orthogonality of the field, improving smoothness and tangent alignment. Our frame fields can serve as a drop-in replacement for frame field optimizations used in previous work, improving the quality of the final vectorizations.CCS Concepts: Computing methodologies -> Parametric curve and surface models; Shape analysisComputing methodologiesParametric curve and surface modelsShape analysis10.1111/cgf.1490115 pages