A Curvature Estimation for Pen Input Segmentation in Sketch-based Modeling

Dae Hyun Kim and Myoung-Jun Kim

Summary

Kim and Kim present a corner finding algorithm which can be used on-the-fly by using local curvature information. The authors first resample the stroke to have equidistant points, and then compute curvature estimates for each resampled point using differential geometry. The local curvature information used are local convexity and local monotonicity. Points are considered locally convex when the sign of the curvature value across a series of points does not change. Local montonicity determines if a series of points are continually decreasing. The algorithm proposed by the authors local monotonicity must be a threshold requirement in order to explore points as possible corners. Local maximum for positive curvature and local minimum for negative curvature are used to select corners.

Evaluations were conducted to see how different drawing styles affected the algorithm, how different approaches (curvature estimation only, local convexity only, local convexity and local monotonicity, and a bending function from Fu et al.), and how the algorithm performs under a some special test cases.

Discussion

The approach is interesting and seems to work well for both polyline and arcs. The on-the-fly aspect seems beneficial in some cases. Although in most cases, a sketch doesn't need to be recognized until it is fully drawn. By not comparing their algorithm to other approaches, the evaluation is questionable to me. While their algorithm may perform well on their test set, another approach could perform even better. Without this evaluation, they can't truly validate this approach as improvement or alternative to the other corner finding algorithms.