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We propose a simple yet effective method to orient normals for point clouds. Central to our approach is a novel optimization objective function defined from global and local perspectives. Globally, we introduce a signed uncertainty function that ...

Estimating consistently oriented normals for point clouds enables a number of important applications in computer graphics such as surface reconstruction. While local normal estimation is possible with simple techniques like principal component analysis (...

Correctly and consistently orienting a set of normal vectors associated with a point cloud sampled from a surface in 3D is a difficult procedure necessary for further downstream processing of sampled 3D geometry, such as surface reconstruction and ...

Estimating normals with globally consistent orientations for a raw point cloud has many downstream geometry processing applications. Despite tremendous efforts in the past decades, it remains challenging to deal with an unoriented point cloud with ...