hasNewKeyFrame

Check if new key frame added in visual SLAM object

Since R2023b

Syntax

hasAdded = hasNewKeyFrame(vslam)

Description

hasAdded = hasNewKeyFrame(vslam) returns a logical value that indicates if a new key frame has been added within the visual simultaneous localization and mapping (vSLAM) object vslam.

Examples

Monocular Visual SLAM Using TUM RGB-D Data Set

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 = "https://cvg.cit.tum.de/rgbd/dataset/freiburg3/rgbd_dataset_freiburg3_long_office_household.tgz"; 
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  
    mkdir(dataFolder) 
    disp("Downloading fr3_office.tgz (1.38 GB). This download can take a few minutes.") 
    websave(tgzFileName,baseDownloadURL,options); 
    
    % Extract contents of the downloaded file
    disp("Extracting fr3_office.tgz (1.38 GB) ...") 
    untar(tgzFileName,dataFolder); 
end

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)
    addFrame(vslam,readimage(imds,i))

    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
        plot(vslam);
    end

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

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)
        plot(vslam);
    end
end

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
reset(vslam)

Input Arguments

vslam — Visual SLAM object

monovslam object

Visual SLAM object, specified as a monovslam object.

Output Arguments

hasAdded — New key frame status

false or 0 | true or 1

New key frame status, returned as 0 (false) or 1 (true). A value of true indicates that a new key frame has been added within the visual SLAM object vslam. A value of false indicates that no new key frame has been added. The object considers an image frame to be a key frame if the number of tracked feature points in the current frame satisfies one of these conditions:

• The number of tracked feature points is within the limits specified by the TrackFeatureRange property of the monovslam object, vslam.

• The number of tracked feature points is greater than the upper limit specified by the TrackFeatureRange property of the monovslam object, vslam, and the number of skipped frames since adding the last key frame equals the value of the SkipMaxFrames.

The hasNewKeyFrame object function returns true once per new key frame added. For example, if the monovslam object adds only one key frame, then two consecutive calls to hasNewKeyFrame return true and false, respectively.

Version History

Introduced in R2023b