Name
Abstract | ||
|---|---|---|
Normal estimation is an essential task for scanned point clouds in various CAD/CAM applications. Many existing methods are unable to reliably estimate normals for points around sharp features since the neighborhood employed for the normal estimation would enclose points belonging to different surface patches across the sharp feature. To address this challenging issue, a robust normal estimation method is developed in order to effectively establish a proper neighborhood for each point in the scanned point cloud. In particular, for a point near sharp features, an anisotropic neighborhood is formed to only enclose neighboring points located on the same surface patch as the point. Neighboring points on the other surface patches are discarded. The developed method has been demonstrated to be robust towards noise and outliers in the scanned point cloud and capable of dealing with sparse point clouds. Some parameters are involved in the developed method. An automatic procedure is devised to adaptively evaluate the values of these parameters according to the varying local geometry. Numerous case studies using both synthetic and measured point cloud data have been carried out to compare the reliability and robustness of the proposed method against various existing methods. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1016/j.cad.2013.06.003 | Computer-Aided Design |
Keywords | Field | DocType |
existing method,normal estimation,enclose neighboring point,adaptive normal estimation method,point cloud data,surface patch,sharp feature,sparse point cloud,neighboring point,developed method,scanned point cloud | CAD,Computer vision,Mathematical optimization,Outlier,Robustness (computer science),Artificial intelligence,Point cloud,Normal estimation,Mathematics | Journal |
Volume | Issue | ISSN |
45 | 11 | 0010-4485 |
Citations | PageRank | References |
9 | 0.48 | 40 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yutao Wang | 1 | 107 | 10.67 |
| Hsi-yung Feng | 2 | 152 | 15.49 |
| Félix-ítienne Delorme | 3 | 9 | 0.48 |
| Serafettin Engin | 4 | 9 | 0.48 |