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Calibration and Data Conversion Tools

To use the data for 3D reconstruction we need to calibrate the camera and also calculate the transform between IMU and camera. For this there is a docker Image running Kalibr included which understands the proto format.

Move the data

To move the data from your device, mount the phone to your filesystem and you will find all data at /Android/data/se.lth.math.videoimucapture/files/YYYY_MM_DD_hh_mm_ss. We now refer to <path-to-recording> as the path to one measurement <my-data-path>/YYYY_MM_DD_hh_mm_ss.

Clone repository

To use the scripts you first need to clone this repository.

git clone https://github.com/DavidGillsjo/VideoIMUCapture-Android.git
cd VideoIMUCapture-Android/calibration

Run Docker container

The easy way to run the docker image is to pull it from Dockerhub. The only prerequisite is that you have docker installed. Start a container by running

DATA=<my-data-path> ./run_dockerhub.sh

If you require sudo to run you may use SUDO=1 DATA=<my-data-path> ./run_dockerhub.sh

You are now in the container and may execute the scripts in this folder or any Kalibr command. Your data will now be mounted under /data, so <path-to-recording>=/data/YYYY_MM_DD_hh_mm_ss.

Calibrate Camera

Calibration of the camera will yield intrinsic camera parameters and distortion parameters. Both might be supplied by the Smartphone depending on brand and model. To see if this is the case, record a short video run

python data2statistics.py /host_home/<path-to-recording>/video_meta.pb3

and look for intrinsic_params and distortion_params.

It is most likely so that they are not available or not good enough. There are many toolboxes for calibrating the camera, we used Kalibr. See below for instructions on how to use Kalibr or MATLAB.

Kalibr

See their instruction on how to perform the calibration.

To convert the video to images you may use

python data2kalibr.py <path-to-recording>
  --tag-size <measured-april-tag-size-in-meters>
  --subsample 30

to convert every 30th frame to an image. (1 image per second)

Assuming we use the Equidistance distortion model the calibration command might look like this

cd <path-to-recording>/kalibr
kalibr_calibrate_cameras --bag kalibr.bag --target target.yaml --models pinhole-equi --topics /cam0/image_raw

Your calibration will end up in <path-to-recording>/kalibr/camchain-kalibr.yaml.

MATLAB

It is possible to use MATLAB for camera calibration. See their instruction for usage. Compute tangential distortion and 2 coefficient radial distortion. When done with the calibration you press Export Parameters and save to your workspace. Then you may use the script we included to store them as a txt file:

cd <path-to-VideoIMUCapture-Android>/calibration
intrinsic2txt(cameraParams, <calibration-result-dir>)

Now you will have the calibration in <calibration-result-dir>/camera.txt.

Calibrate IMU and camera

Now we need the transform between IMU and camera. For this we use Kalibr. See their instruction on how to perform the calibration. Note that this should be a different dataset than for calibration of the camera, since they have different requirements.

To convert the recording to their ROS-format and prepare necessary files you may use the supplied script

python data2kalibr.py <path-to-recording>
  --tag-size <measured-april-tag-size-in-meters>
  --subsample 3
  # If you have MATLAB camera calibration
  --matlab-calibration <calibration-result-dir>/camera.txt
  # If you have Kalibr camera calibration
  --kalibr-calibration <calibration-result-dir>/camchain-kalibr.yaml

which will put the required files in <path-to-recording>/kalibr

To start the calibration run

cd <path-to-recording>/kalibr
kalibr_calibrate_imu_camera
  --target target.yaml
  --imu imu.yaml
  --cams camchain.yaml
  --bag kalibr.bag

and you will find the calibration result at camchain-imucam-kalibr.yaml together with report report-imucam-kalibr.pdf.

Convert data to rosbag

To convert a recording to rosbag you may use

python data2rosbag.py <path-to-recording>
  --calibration camchain-imucam-kalibr.yaml # Will copy calibration file and re-scale it to current video resolution.
  --raw-image                               # Store raw images instead of compressed

The script will crawl through <path-to-recording>, so it may also be a directory with sub-directories containing recordings. See help for more details

python data2rosbag.py --help

Build and run local Docker Image (Development)

In case you want to build the image yourself to customize it. First build the image by running

./build_docker.sh

If you require sudo to run you may use SUDO=1 ./build_docker.sh

Then start a container by running

./run_docker.sh

If you require sudo to run or want to mount a different directory than $HOME you may use SUDO=1 DHOME=<custom_home> ./run_docker.sh

For a full list of options see dockers README.

For development purposes, you most likely want to use the code on host instead of container copy. From within the docker you may now navigate to this folder, if you cloned it to $HOME/VideoIMUCapture-Android then you run

cd /host_home/VideoIMUCapture-Android/calibration

to go to this folder from within the docker container.