@@ -331,17 +331,17 @@ infinite value. It also removes the corresponding attributes.
331
331
pointcloud.def (
332
332
" orient_normals_consistent_tangent_plane" ,
333
333
&PointCloud::OrientNormalsConsistentTangentPlane, " k" _a,
334
- " lambda " _a = 0.0 , " cos_alpha_tol" _a = 1.0 ,
334
+ " lambda_penalty " _a = 0.0 , " cos_alpha_tol" _a = 1.0 ,
335
335
R"( Function to consistently orient the normals of a point cloud based on tangent planes.
336
336
337
337
The algorithm is described in Hoppe et al., "Surface Reconstruction from Unorganized Points", 1992.
338
- Additional information about the choice of lambda and cos_alpha_tol for complex
338
+ Additional information about the choice of lambda_penalty and cos_alpha_tol for complex
339
339
point clouds can be found in Piazza, Valentini, Varetti, "Mesh Reconstruction from Point Cloud", 2023
340
340
(https://eugeniovaretti.github.io/meshreco/Piazza_Valentini_Varetti_MeshReconstructionFromPointCloud_2023.pdf).
341
341
342
342
Args:
343
343
k (int): Number of neighbors to use for tangent plane estimation.
344
- lambda (float): A non-negative real parameter that influences the distance
344
+ lambda_penalty (float): A non-negative real parameter that influences the distance
345
345
metric used to identify the true neighbors of a point in complex
346
346
geometries. It penalizes the distance between a point and the tangent
347
347
plane defined by the reference point and its normal vector, helping to
@@ -354,7 +354,7 @@ point clouds can be found in Piazza, Valentini, Varetti, "Mesh Reconstruction fr
354
354
Example:
355
355
We use Bunny point cloud to compute its normals and orient them consistently.
356
356
The initial reconstruction adheres to Hoppe's algorithm (raw), whereas the
357
- second reconstruction utilises the lambda and cos_alpha_tol parameters.
357
+ second reconstruction utilises the lambda_penalty and cos_alpha_tol parameters.
358
358
Due to the high density of the Bunny point cloud available in Open3D a larger
359
359
value of the parameter k is employed to test the algorithm. Usually you do
360
360
not have at disposal such a refined point clouds, thus you cannot find a
@@ -379,7 +379,7 @@ point clouds can be found in Piazza, Valentini, Varetti, "Mesh Reconstruction fr
379
379
poisson_mesh.compute_vertex_normals()
380
380
o3d.visualization.draw_geometries([poisson_mesh])
381
381
382
- # Case 2, reconstruction using lambda and cos_alpha_tol parameters:
382
+ # Case 2, reconstruction using lambda_penalty and cos_alpha_tol parameters:
383
383
pcd_robust = o3d.io.read_point_cloud(data.path)
384
384
385
385
# Compute normals and orient them consistently, using k=100 neighbours
0 commit comments