Polylidar -- Polygons from Triangular Meshes
This addresses the need for efficient polygon extraction in applications like mapping and visualization, but it is incremental as it builds on existing triangulation and filtering techniques.
The paper tackles the problem of extracting non-convex polygons with holes from 2D point sets, such as plane-segmented point clouds, to reduce map size and improve visualization, achieving comparable accuracy and over four times speedup compared to other methods.
This paper presents Polylidar, an efficient algorithm to extract non-convex polygons from 2D point sets, including interior holes. Plane segmented point clouds can be input into Polylidar to extract their polygonal counterpart, thereby reducing map size and improving visualization. The algorithm begins by triangulating the point set and filtering triangles by user configurable parameters such as triangle edge length. Next, connected triangles are extracted into triangular mesh regions representing the shape of the point set. Finally each region is converted to a polygon through a novel boundary following method which accounts for holes. Real-world and synthetic benchmarks are presented to comparatively evaluate Polylidar speed and accuracy. Results show comparable accuracy and more than four times speedup compared to other concave polygon extraction methods.