STAR-Edge: Structure-aware Local Spherical Curve Representation for Thin-walled Edge Extraction from Unstructured Point Clouds

MFLE EC-Net (a) (f) (b) (c) large neighborhood (d) small neighborhood upper face lower face side face near edge (e) Local spherical projection Figure 1. The characteristics of our method and visual comparison of edge extraction results in thin-walled structures. (a) defines the concept of a thin-walled edge. (b) highlights that the primary challenge in thin-walled edge extraction is the sensitivity to local neighborhood selection. (c) illustrates how a larger neighborhood may include points from both upper and lower surfaces as well as side-end faces, blurring boundary information. (d) shows that a smaller neighborhood may suffer from noise and insufficient sampling on side faces, lacking the contextual information needed for accurate edge point recognition. (e) depicts the spherical projection of the local neighborhood of four points, where points of the same color lie on the same underlying surface. This illustrates our key observation that points co-planar with the neighborhood center tend to align along a great circle arc after spherical projection. (f) provides a qualitative comparison of our STAR-Edge with RFEPS [29], EC-Net [32], and MFLE [4].