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findPointsInModel

Find points in or on surface of geometric model

Since R2024a

    Description

    example

    indices = findPointsInModel(model,ptCloud) finds the points in the point cloud ptCloud that are located inside or on the surface of the geometric shape specified by model, and returns their linear indices.

    Examples

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    Load a MAT file containing point cloud data into the workspace.

    load("object3d.mat")

    Visualize the point cloud.

    figure
    pcshow(ptCloud)

    Define a region of interest (ROI) in the point cloud in which to detect a cylinder model.

    roi = [0.4 0.7; -0.1 0.2; 0 0.4];
    sampleIndices = findPointsInROI(ptCloud,roi);

    Set a maximum point-to-cylinder distance of 5 mm for cylinder fitting and the orientation constraint.

    maxDistance = 0.005;
    referenceVector = [0 0 1];

    Detect a cylinder in the point cloud.

     model = pcfitcylinder(ptCloud,maxDistance,referenceVector, ...
            SampleIndices=sampleIndices);

    Create a synthetic point cloud that is evenly distributed and covers the region of interest.

    gridStep = 0.005;
    [x,y,z] = meshgrid(roi(1,1):gridStep:roi(1,2),roi(2,1):gridStep:roi(2,2), ...
    roi(3,1):gridStep:roi(3,2));
    syntheticPtCloud = pointCloud([x(:) y(:) z(:)],Color=[0.7 0.7 0.8]);

    Find the points in the synthetic point cloud that are in the cylinder.

    idx = findPointsInModel(model,syntheticPtCloud);
    cylinderPtCloud = select(syntheticPtCloud,idx);

    Visualize the resulting point cloud, with the synthetic points in the cylinder modeling the object on the table.

    figure
    pcshow(cylinderPtCloud)
    hold on
    pcshow(ptCloud)

    Load a MAT file containing a point cloud into the workspace.

    load("object3d.mat")

    Visualize the point cloud.

    figure
    pcshow(ptCloud)

    Define a region of interest (ROI) in the point cloud in which to detect a sphere model.

    roi = [0.2 0.55; 0.2 0.5; 0 0.5];
    sampleIndices = findPointsInROI(ptCloud,roi);

    Set a maximum point-to-sphere distance of 5mm for sphere fitting.

    maxDistance = 0.005;

    Detect the sphere in the point cloud.

    [model,inlierIdx] = pcfitsphere(ptCloud,maxDistance,SampleIndices=sampleIndices);

    Find one of the colors in the detected sphere, to use for the synthetic point cloud.

    inlierPtCloud = select(ptCloud,inlierIdx);
    color = median(inlierPtCloud.Color);

    Create a synthetic point cloud that is evenly distributed and covers the region of interest.

    gridStep = 0.005;
    [x,y,z] = meshgrid(roi(1,1):gridStep:roi(1,2),roi(2,1):gridStep:roi(2,2), ...
    roi(3,1):gridStep:roi(3,2));
    syntheticPtCloud = pointCloud([x(:) y(:) z(:)],Color=color);

    Find the points in the synthetic point cloud that are in the sphere.

    idx = findPointsInModel(model,syntheticPtCloud);
    spherePtCloud = select(syntheticPtCloud,idx);

    Visualize the resulting point cloud, with the synthetic points in the sphere modeling the object on the table.

    figure
    pcshow(spherePtCloud)
    hold on
    pcshow(ptCloud)

    Input Arguments

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    Parametric model, specified as a cylinderModel or sphereModel object.

    Point cloud in the sensor coordinate system, specified as a pointCloud object.

    Output Arguments

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    Linear indices of the point cloud points that are located inside or on the surface of the model, returned as a column vector.

    Version History

    Introduced in R2024a

    See Also

    Objects