addFrame
Description
addFrame(
adds the pair of color and depth images, vslam
,colorImage
,depthImage
)colorImage
and
depthImage
respectively, to the RGB-D visual SLAM object
vslam
. The color and depth images must be preregistered with a
one-to-one correspondence.
Note
The rgbdvslam
object runs on multiple threads internally, which can delay the processing of an image frame added by using the addFrame
function. Additionally, the object running on multiple threads means the current frame the object is processing can be different than the recently added frame.
Examples
Perform RGB-D 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://vision.in.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 two imageDatastore
objects. One to store the color images and the other to store the depth images.
colorImageFolder = dataFolder+"rgbd_dataset_freiburg3_long_office_household/rgb/"; depthImageFolder = dataFolder+"rgbd_dataset_freiburg3_long_office_household/depth/"; imdsColor = imageDatastore(colorImageFolder); imdsDepth = imageDatastore(depthImageFolder);
Select the synchronized pair of color and depth images.
data = load("rgbDepthPairs.mat");
imdsColor=subset(imdsColor, data.indexPairs(:, 1));
imdsDepth=subset(imdsDepth, data.indexPairs(:, 2));
Specify your camera intrinsic parameters, and use them to create an RGB-D visual SLAM object.
intrinsics = cameraIntrinsics([535.4 539.2],[320.1 247.6],[480 640]); depthScaleFactor = 5000; vslam = rgbdvslam(intrinsics,depthScaleFactor);
Process each pair of color and depth images, and visualize the camera poses and 3-D map points.
for i = 1:numel(imdsColor.Files) colorImage = readimage(imdsColor,i); depthImage = readimage(imdsDepth,i); addFrame(vslam,colorImage,depthImage); 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); % Stop adding frames when tracking is lost if status == uint8(0) break end end
Once all the frames have been processed, reset the system.
while ~isDone(vslam) plot(vslam); end
reset(vslam);
Perform RGB-D visual-inertial SLAM using the data from the OpenLORIS-Scene Dataset. Download the data to a temporary directory using a web browser or by running this code:
dataFolder = fullfile(tempdir,"OpenLORIS-Scene",filesep); downloadURL = "https://ssd.mathworks.com/supportfiles/shared_nav_vision/data/OpenLORIS-Scene_corridor1-4.zip"; zipFileName = dataFolder+"corridor1-4.zip"; if ~isfolder(dataFolder) mkdir(dataFolder); disp("Downloading corridor1-4.zip (1.13 GB). This download can take a few minutes."); options = weboptions('Timeout', Inf); websave(zipFileName, downloadURL, options); unzip(zipFileName, dataFolder); end
Create two imageDatastore
objects. One to store the color images and the other to store the depth images.
imageFolder = fullfile(dataFolder,"OpenLORIS-Scene_corridor1-4"); imdsColor = imageDatastore(fullfile(imageFolder,"color")); imdsDepth = imageDatastore(fullfile(imageFolder,"aligned_depth"));
Load the IMU measurements data and the camera-to-IMU transform.
data = load("corridor4_IMU_data.mat");
gyro = data.gyroDataCell;
accel = data.accelDataCell;
cam2IMU = data.cam2IMU;
Specify the camera intrinsics, the IMU parameters, and use them to create an RGB-D visual-inertial SLAM object.
% Camera intrinsic and IMU parameters can be found in the downloaded % sensors.yaml file intrinsics = cameraIntrinsics([6.1145098876953125e+02, 6.1148571777343750e+02],... [4.3320397949218750e+02, 2.4947302246093750e+02], [480, 848]); imuParams = factorIMUParameters(AccelerometerBiasNoise=2.499999936844688e-05*eye(3),... AccelerometerNoise=0.00026780980988405645*eye(3),... GyroscopeNoise=1.0296060281689279e-05*eye(3),... GyroscopeBiasNoise=2.499999993688107e-07*eye(3),... SampleRate=250); depthScaleFactor = 1000; vslam = rgbdvslam(intrinsics, depthScaleFactor, imuParams, SkipMaxFrames=10,... CameraToIMUTransform=cam2IMU, TrackFeatureRange = [30, 150], DepthRange= [0.1, 6.5], ... NumPosesThreshold=20, MaxNumPoints=1.2e3);
Process image data and IMU data, and visualize the camera poses and 3-D map points.
for i = 1:numel(imdsColor.Files) colorImage = readimage(imdsColor,i); depthImage = readimage(imdsDepth,i); addFrame(vslam, colorImage, depthImage, gyro{i}, accel{i}); if hasNewKeyFrame(vslam) plot(vslam); end end
Once all the frames have been processed, reset the system.
while ~isDone(vslam) if hasNewKeyFrame(vslam) ax = plot(vslam); end end view(ax, 0, 90)
reset(vslam);
Input Arguments
RGB-D visual SLAM object, specified as an rgbdvslam
object.
Color image, specified as a nonsparse RGB or grayscale image. The color and depth images must be preregistered with a one-to-one correspondence.
Data Types: single
| double
| int16
| uint8
| uint16
| logical
Color image, specified as a nonsparse grayscale image. The color and depth images must be preregistered with a one-to-one correspondence.
Data Types: single
| double
| int16
| uint8
| uint16
| logical
Gyroscope measurement, specified as an N-by-3 matrix. Each row of the matrix represents the x, y, and z components of the gyroscope measurement for a single frame, of the form [gx,gy,gz]. N represents the total number of frames. N represents the number of IMU measurements between the previous and current camera frames. The number of gyroscope and accelerometer measurements must be equal.
Acceleration measurement, specified as an N-by-3 matrix. Each row of the matrix represents the x, y, and z components of the acceleration measurement for a single frame, of the form [ax,ay,az]. N represents the number of IMU measurements between the previous and current camera frames. The number of gyroscope and accelerometer measurements must be equal.
Version History
Introduced in R2024a
See Also
Objects
Functions
hasNewKeyFrame
|checkStatus
|isDone
|mapPoints
|poses
|plot
|reset
Topics
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