pointCloud

R2026b

Sparse 3-D scene point cloud reconstructed using structure-from-motion (SfM)

Since R2026b

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Syntax

ptCloud = pointCloud(sfmObj)

Description

ptCloud = pointCloud(sfmObj) returns the sparse 3-D point cloud reconstructed from the scene views associated with the sfm object, sfmObj. Use this function to retrieve 3_D scene point cloud after calling the triangulateInitialViews or reconstruct object function. The point cloud returned after calling the reconstruct object function is more complete than the one produced after triangulateInitialViews, which only contains triangulated points for the initial two views.

example

Examples

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Open Live Script

Use the sfm object to recover camera poses and a sparse 3-D point cloud from images of an indoor scene.

Create Image Datastore and Define Camera Intrinsics

Create an ImageDatastore from the image sequence. Specify the camera intrinsic parameters.

unzip("sfm_images.zip")
imageFolder = fullfile(pwd,"images");
imds = imageDatastore(imageFolder);
intrinsics = cameraIntrinsics([535.1307 532.1860],[323.3722 239.7986],[480 640]);

Visualize the indoor scene.

imshow(preview(imds))

Create SfM Object and Run Pipeline

Create an sfm object and execute each stage of the incremental SfM pipeline sequentially.

sfmObj = sfm(imds,intrinsics);

Connect image pairs based on visual similarity.

sfmObj = connectImagePairs(sfmObj);

Visualize the similarity matrix for the connected image pairs using the imagesc function.

imagesc(sfmObj.SimilarityMatrix)
title("Similarity Matrix for Connected Image Pairs")

Verify that the view graph was created successfully before proceeding to geometric verification.

if isConnected(sfmObj)
    sfmObj = verifyImagePairs(sfmObj);
end

Visualize the similarity matrix for the refined image pair connections using the imagesc function.

imagesc(sfmObj.SimilarityMatrix)
title("Similarity Matrix after Refining Connected Image Pairs")

Confirm that geometric verification completed successfully before initializing the reconstruction. Specify a minimum median angle of 5 degrees and a maximum triangulation error of 4 pixels. Display the initialization metrics.

if isVerified(sfmObj)
    [sfmObj,info] = triangulateInitialViews(sfmObj,MinMedianAngle=5,MaxTriangulationError=4);
    disp(info)
end
                     ViewId1: 9
                     ViewId2: 10
                RelativePose: [1×1 rigidtform3d]
                     Matches: [380×2 uint32]
    MedianTriangulationAngle: 8.6016
       MeanReprojectionError: 0.2799

Confirm that initialization succeeded before running incremental reconstruction.

if isInitialized(sfmObj)
    sfmObj = reconstruct(sfmObj);
end

Retrieve Results

Retrieve the estimated camera poses and the sparse 3-D point cloud.

camPoses = poses(sfmObj);
sparsePoints = pointCloud(sfmObj);

Visualize Reconstruction

Display the reconstructed scene showing the camera trajectory and sparse point cloud. Adjust the view orientation and zoom for better visualization.

plot(sfmObj,CameraSize=0.5,MarkerSize=25)
view(82.69,-15.53)
camroll(-90)
camva(4.52)

Input Arguments

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Structure from motion object, specified as an sfm object. The object must contain triangulated 3-D points generated by running triangulateInitialViews or reconstruct object functions.

Output Arguments

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Sparse 3-D reconstruction, returned as a pointCloud object. Using the pointCloud object, you can access the 3-D coordinates from the Location property and the point colors using the Color property.

Version History

Introduced in R2026b

See Also

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