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End-of-processing status for visual SLAM object

Since R2023b



done = isDone(vslam) returns a logical value indicating whether the visual SLAM object has finished processing its frames. A value of true indicates the object is in an idle state. A value of false indicates the object is processing one or more frames.


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Perform monocular visual simultaneous localization and mapping (vSLAM) using the data from the TUM RGB-D Benchmark. You can download the data to a temporary directory using a web browser or by running this code:

baseDownloadURL = ""; 
dataFolder = fullfile(tempdir,"tum_rgbd_dataset",filesep); 
options = weboptions(Timeout=Inf);
tgzFileName = dataFolder+"fr3_office.tgz";
folderExists = exist(dataFolder,"dir");

% Create a folder in a temporary directory to save the downloaded file
if ~folderExists  
    disp("Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.") 
    % Extract contents of the downloaded file
    disp("Extracting fr3_office.tgz (1.38 GB) ...") 

Create an imageDatastore object to store all the RGB images.

imageFolder = dataFolder+"rgbd_dataset_freiburg3_long_office_household/rgb/";
imds = imageDatastore(imageFolder);

Specify your camera intrinsic parameters, and use them to create a monocular visual SLAM object.

intrinsics = cameraIntrinsics([535.4 539.2],[320.1 247.6],[480 640]);
vslam = monovslam(intrinsics);

Process each image frame, and visualize the camera poses and 3-D map points.

for i = 1:numel(imds.Files)

    if hasNewKeyFrame(vslam)
        % Query 3-D map points and camera poses
        xyzPoints = mapPoints(vslam);
        [camPoses,viewIds] = poses(vslam);

        % Display 3-D map points and camera trajectory

    % Get current status of system
    status = checkStatus(vslam);

Figure contains an axes object. The axes object with xlabel X, ylabel Y contains 12 objects of type line, text, patch, scatter. This object represents Camera trajectory.

Note that the monovslam object runs several algorithm parts on separate threads, which can introduce a latency in processing of an image frame added by using the addFrame function.

% Plot intermediate results and wait until all images are processed
while ~isDone(vslam)
    if hasNewKeyFrame(vslam)

After all the images are processed, you can collect the final 3-D map points and camera poses for further analysis.

xyzPoints = mapPoints(vslam);
[camPoses,viewIds] = poses(vslam);

% Reset the system

Input Arguments

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Visual SLAM object, specified as a monovslam object.

Version History

Introduced in R2023b