"Eliminating False Positives During Corner Finding by Merging Similar Segments"

by Aaron Wolin, Brandon Paulson, Tracy Hammond

Summary

This paper introduces MergeCF, which utilizes stroke's curvature and drawing speed to find corners in sketches. Then false positive corners are removed and segments that are alike are merged.

Distances: Chord distance (euclidean distance) and path length.
Speed: Speed at Pi is path length / duration for the neighborhood Pi-1 to Pi+1.

Initial fit: Corners are points with high curvature and low speed. Also check corners that are close together and remove those with smallest curvature.

Merging segments: Corners surrounding the smallest stroke segments are likely to be false
positives. Find the smallest segment, than combine it with one of its neighbors that yields smaller primitive fit error. No merging is performed if the error after merging is much higher than the sum of original errors of the two segments.

Experiment using polylines and complex shapes shows that Merge outperforms Sezgin and Kim on both "correct corner found" accuracy (0.971 vs 0.822 & 0.783) and all-or-nothing accuracy (0.667 vs 0.298 & 0.194).


Discussion

This algorithm first find as many potential corners as possible and then eliminate false positives. The important part is how to define the threshold for "small segment" and "not much higher error".