Feature Extraction From Point Clouds

This paper describes a new method to extract feature lines directly from a surface point cloud. No surface reconstruction is needed in advance, only the inexpensive computation of a neighbor graph connecting nearby points. The feature extraction is performed in two stages. The first stage constists of assigning a penalty weight to each point that indicates the unlikelihood that the point is part of a feature and assigning these penalty weights to the edges of a neighbor graph. Extracting a subgraph of the neighbor graph that minimizes the edge penalty weights then produces a set of feature patterns. The second stage is especially useful for noisy data. It recovers feature lines and junctions by fitting wedges to the crease lines and corners to the junctions. As the method works on the local neighbor graph only, it is fast and automatically adapts to the sampling resolution. This makes the approach ideal as a preprocessing step in mesh generation. CR Categories: I.4.6 Segmentation [Edge and feature detection]—;