pcnormals

R2026b

Estimate normals for point cloud

Syntax

normals = pcnormals(ptCloud)

normals = pcnormals(ptCloud,k)

Description

normals = pcnormals(ptCloud) returns a matrix that stores a normal for each point in the input ptCloud. The function uses six neighboring points to fit a local plane to determine each normal vector.

normals = pcnormals(ptCloud,k) additionally specifies k, the number of points used for local plane fitting. The function uses this value rather than the six neighboring points as described in the first syntax.

Examples

Estimate Normals of Point Cloud

Load a point cloud.

load('object3d.mat');

Estimate the normal vectors.

normals = pcnormals(ptCloud);

figure
pcshow(ptCloud)
title('Estimated Normals of Point Cloud')
hold on

x = ptCloud.Location(1:10:end,1:10:end,1);
y = ptCloud.Location(1:10:end,1:10:end,2);
z = ptCloud.Location(1:10:end,1:10:end,3);
u = normals(1:10:end,1:10:end,1);
v = normals(1:10:end,1:10:end,2);
w = normals(1:10:end,1:10:end,3);

Plot the normal vectors.

quiver3(x,y,z,u,v,w);
hold off

Flip the normals to point towards the sensor location. This step is necessary only for determining the inward or outward direction of the surface. The sensor center is set in x , y , z coordinates.

sensorCenter = [0,-0.3,0.3]; 
for k = 1 : numel(x)
   p1 = sensorCenter - [x(k),y(k),z(k)];
   p2 = [u(k),v(k),w(k)];
   % Flip the normal vector if it is not pointing towards the sensor.
   angle = atan2(norm(cross(p1,p2)),p1*p2');
   if angle > pi/2 || angle < -pi/2
       u(k) = -u(k);
       v(k) = -v(k);
       w(k) = -w(k);
   end
end

Plot the adjusted normals.

figure
pcshow(ptCloud)
title('Adjusted Normals of Point Cloud')
hold on
quiver3(x, y, z, u, v, w);
hold off

Input Arguments

ptCloud — Object for storing point cloud

pointCloud object

Object for storing point cloud, returned as a pointCloud object.

k — Number of points used for local plane fitting

integer greater than or equal to 3

Number of points used for local plane fitting, specified as an integer greater than or equal to 3. Increasing this value improves accuracy but slows down computation time. If you do not specify k, the function uses six neighboring points to fit a local plane to determine each normal vector.

Output Arguments

normals — Normals used to fit a local plane

M-by-3 matrix | M-by-N-by-3 matrix

Normals used to fit a local plane, returned as an M-by-3 or an M-by-N-by-3 matrix. The normal vectors are computed locally using the number of neighbors defined by the value of k. If k is not an input, it uses six neighboring points. The direction of each normal vector can be set based on how you acquired the points. The Estimate Normals of Point Cloud example, shows how to set the direction when the normal vectors are pointing towards the sensor.

References

[1] Hoppe, H., T. DeRose, T. Duchamp, J. Mcdonald, and W. Stuetzle. "Surface Reconstruction from Unorganized Points". Computer Graphics (SIGGRAPH 1992 Proceedings). 1992, pp. 71–78.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

GPU Code Generation

Generate CUDA® code for NVIDIA® GPUs using GPU Coder™.

Usage notes and limitations:

• For GPU code generation, the number of neighbors must be a compile-time constant.

• Because of architectural and implementation differences between the GPU and CPU, the choice of neighboring points may differ during computation of normal vectors. As a result, there may be numerical mismatch between MATLAB^® simulation and the output from code generation.

Version History

Introduced in R2015b

R2026b: Moved to Point Cloud Toolbox from Computer Vision Toolbox

Starting in R2026b, pcnormals is available in Point Cloud Toolbox™. In releases R2026a and before, pcnormals is available in Computer Vision Toolbox™.