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pcnormals

Estimate normals for point cloud

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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.

example

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

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Open Live Script

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

Figure contains an axes object. The axes object with title Estimated Normals of Point Cloud contains an object of type scatter.

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

Figure contains an axes object. The axes object with title Estimated Normals of Point Cloud contains 2 objects of type scatter, quiver.

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

Figure contains an axes object. The axes object with title Adjusted Normals of Point Cloud contains 2 objects of type scatter, quiver.

Input Arguments

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

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

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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™.

Version History

Introduced in R2015b

See Also

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