Camera-to-IMU calibration and synchronization toolbox
This toolbox provides a python library to perform joint calibration of a rolling shutter camera-gyroscope system.
Given gyroscope and video data, this library can find the following parameters
If you use the package for your work, please cite the following paper
Ovrén, H and Forssén, P.-E. "Gyroscope-based video stabilisation with auto-calibration." In 2015 IEEE International Conference on Robotics and Automation (ICRA) (pp. 2090–2097). Seattle, WA
The calibration methods in this package assumes the following
If the video and gyroscope data are not uniformly sampled, but you have access to somewhat reliable timestamps, then you can still use the method if you resample the data to be uniform. By "reliable" we mean timestamps without drift, and no (or negligble) jitter.
The 2.0 version of crisp features a new fully automatic calibrator. This means that there is no compelling reason to use the semi-manual methods in the previous version of crisp. Therefore the old example scripts have been removed, and the old functions are not imported into the module namespace. No old functions have been removed, so if you want to use them they are still available in submodules.
To use the package you need the following Python packages:
The easiest way is to install from PyPI:
$ pip install crisp
If you want to build the package from source, you also need the Cython package. To build and install the
crispmodule just run the following commands:
$ python setup.py build $ python setup.py install
For a user-only installation add
--userto the install command.
The gyroscope and video data are first loaded into a stream object (
GyroStream, and a subclass of
VideoStreamrespectively). To be able to understand how points are mapped from the real world to the image, the video stream also need a
gyro = crisp.GyroStream.from_data(some_data_array) camera_model = crisp.AtanCameraModel(...) # One specific choice of camera model video = crisp.VideoStream.from_file(camera_model, video_file_path)
We then tie the streams together using a
AutoCalibratorinstance. Since the calibration proces need to have estimates of the time offset and relative rotation, these are first estimated using the
initialize()member. This initialization only requires that you give an approximate gyroscope sample rate (in Hz).
calibrator = crisp.AutoCalibrator(video, gyro) calibrator.initialize(guessed_gyro_rate) result = calibrator.calibrate() # Dict of calibrated parameters
Initialization and calibration errors can be caught by handling
We bundle one example script
gopro_dataset_example.pywhich shows how to use the library with the data in our dataset (http://www.cvl.isy.liu.se/research/datasets/gopro-gyro-dataset/). This is the same dataset that was used to produce the above mentioned ICRA 2015 paper.
All code in this repository is licensed under the GPL version 3.