Load a set of 3-D coordinate points into the workspace.

load('xyzPoints.mat');

Create a point cloud object.

ptCloud = pointCloud(xyzPoints);

Specify a query point and the radius within which the neighbors are to be identified.

point = [0,0,3];
radius = 0.5;

Get the indices and the distances of points that lie within the specified radius.

[indices,dists] = findNeighborsInRadius(ptCloud,point,radius);

Get the point cloud data of radial neighbors.

ptCloudB = select(ptCloud,indices);

Display the point cloud. Plot the query point and the corresponding radial neighbors.

figure
pcshow(ptCloud)
hold on
plot3(point(1),point(2),point(3),'*')
pcshow(ptCloudB.Location,'r')
legend('Point Cloud','Query Point','Radial Neighbors','Location','southoutside','Color',[1 1 1])
hold off

Find radial neighbors of a query point in the organized point cloud data by using the camera projection matrix. Compute the camera projection matrix from sampled point cloud data points and their corresponding image point coordinates.

Load an organized point cloud data into the workspace. The point cloud is generated by using the Kinect depth sensor.

ld = load('object3d.mat');
ptCloud = ld.ptCloud;

Specify the step size for sampling the point cloud data.

stepSize = 100;

Sample the input point cloud and store the sampled 3-D point coordinates as a point cloud object.

indices = 1:stepSize:ptCloud.Count;
tempPtCloud = select(ptCloud,indices);

Remove invalid points from the sampled point cloud.

[tempPtCloud,validIndices] = removeInvalidPoints(tempPtCloud);

Define the 3-D world point coordinates of input point cloud.

worldPoints = tempPtCloud.Location;

Find the 2-D image coordinates corresponding to the 3-D point coordinates of input point cloud.

[Y,X] = ind2sub([size(ptCloud.Location,1),size(ptCloud.Location,2)],indices);
imagePoints = [X(validIndices)' Y(validIndices)'];

Estimate camera projection matrix from the image and the world point coordinates.

camMatrix = estimateCameraMatrix(imagePoints,worldPoints);

Specify a query point and the radius within which the neighbors are to be identified.

point = [0.4 0.3 0.2];
radius = 0.05;

Get the indices and the distances of radial neighbors. Use the point cloud method select to get the point cloud data of neighboring points.

[indices,dists] = findNeighborsInRadius(ptCloud,point,radius,camMatrix);
ptCloudB = select(ptCloud,indices);

Display the point cloud and the radial neighbors found around a query point.

figure
pcshow(ptCloud);
hold on;
pcshow(ptCloudB.Location, 'b');
legend('Point Cloud','Radial Neighbors','Location','southoutside','Color',[1 1 1] )
hold off;