poses

Absolute camera poses of key frames

Since R2023b

Syntax

camPoses = poses(vslam)

[camPoses,keyFrameIDs] = poses(vslam)

Description

camPoses = poses(vslam) returns the absolute camera poses camPoses of the key frames from the visual simultaneous localization and mapping (vSLAM) object vslam.

[camPoses,keyFrameIDs] = poses(vslam) returns the IDs keyFrameIDs of the key frames corresponding to the camera poses. The IDs represent the order in which the image frames have been added to the vslam object by the addFrame object function.

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,TrackFeatureRange=[30,120]);

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

for i = 1:numel(imds.Files)
    addFrame(vslam,readimage(imds,i))

    if hasNewKeyFrame(vslam)
        % Display 3-D map points and camera trajectory
        plot(vslam);
    end

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

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,addedFramesIdx] = poses(vslam);

% Reset the system
reset(vslam)

Compare the estimated camera trajectory with the ground truth to evaluate the accuracy.

% Load ground truth
gTruthData = load("orbslamGroundTruth.mat");
gTruth     = gTruthData.gTruth;

% Evaluate tracking accuracy
mtrics = compareTrajectories(camPoses, gTruth(addedFramesIdx), AlignmentType="similarity");
disp(['Absolute RMSE for key frame location (m): ', num2str(mtrics.AbsoluteRMSE(2))]);

Absolute RMSE for key frame location (m): 0.093645

% Plot the absolute translation error at each key frame
figure
ax = plot(mtrics, "absolute-translation");
view(ax, [2.70 -49.20]); 

Input Arguments

vslam — Visual SLAM object

monovslam object

Visual SLAM object, specified as a monovslam object.

Output Arguments

camPoses — Absolute camera poses of key frames

M-element array of rigidtform3d objects

Absolute camera poses of key frames, returned as an M-element array of rigidtform3d objects.

keyFrameIDs — Key frame IDs for absolute camera poses

M-element array of integers

Key frame IDs for the absolute camera poses, returned as an M-element array of integers. Each element specifies the key frame ID for the camera pose in the corresponding element of camPoses. The IDs represent the order in which the image frames have been added to the vslam object by the addFrame object function.

Version History

Introduced in R2023b