Pointnormal

Pointnormal is a data representation used in 3D geometry and computer graphics that pairs a spatial point with an associated normal vector. In practice, a pointnormal dataset stores points in three-dimensional space where each point has a corresponding normal describing the local surface orientation at that location. This approach is commonly used in point clouds and related processing pipelines to provide both position and directional information about a surface.

In many software libraries, pointnormal is implemented as a specialized data type. For example, the Point Cloud Library (PCL) provides a PointNormal structure that extends a basic 3D point with normal components (nx, ny, nz) and sometimes curvature. Other frameworks use similar per-point records containing x, y, z, nx, ny, nz, and optional curvature fields. Normals are typically unit vectors that indicate the surface’s outward or upward-facing direction, and they may be oriented globally or locally to ensure consistency across the dataset.

Normals are usually estimated from local neighborhoods. Common approaches involve principal component analysis (PCA) on neighboring points to determine the surface normal, followed by a separate step to orient normals consistently (for example, using region-growing or global optimization). Accurate normals improve the quality of downstream tasks such as shading, rendering, surface reconstruction (e.g., Poisson reconstruction), and point-based alignment or registration.

Pointnormal thus serves as a compact, expressive representation for surfaces captured as point clouds, enabling enhanced geometric processing and visualization while remaining a practical data format across tools and libraries.