Find 3D Normals and Curvature

Fast normal and curvature estimation for sparse point clouds
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Actualizado 14 abr 2015

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Estimates the normals and curvature for a sparse 3D point cloud, by using the n nearest neighbours to approximate a plane at each point.
-Able to process point clouds of over 1 million points in under 60 seconds.
-Robust to flipped normal direction
-Uses a nearest neighbour search (as opposed to a range search) to minimize parameter tuning and allow handling of point clouds with highly non-uniform density.

Citar como

Zachary Taylor (2024). Find 3D Normals and Curvature (https://www.mathworks.com/matlabcentral/fileexchange/48111-find-3d-normals-and-curvature), MATLAB Central File Exchange. Recuperado .

Compatibilidad con la versión de MATLAB
Se creó con R2012a
Compatible con cualquier versión
Compatibilidad con las plataformas
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Versión Publicado Notas de la versión
1.4.0.0

Zip appeared empty, re-uploaded to fix

1.3.0.0

Not using eig gives inaccurate results under some conditions, reverting to previous version till I can track down and fix the issue

1.2.0.0

Abandoned Matlabs eig function in favour of calculating eigenvalues and vectors analytically. Allowed for vectorization of the code and a speed improvement of at least 2x.
Also changed default value of dirLargest to false

1.1.0.0

added demo file

1.0.0.0