MIP - MCC: MIP - MultiCameraCalibration

At the Multimedia Information Processing Group a powerful calibration software has been developed, which is capable to calibrate multiple cameras which are rigidly coupled in one single program (e.g. a stereo rig or a rig with many rigidly coupled cameras). This software is able to calibrate the intrinsic parameters and the extrinsic parameters of all cameras altogether. Additionally 3D-cameras can be calibrated together with the standard camera(s). The 3D-/ToF-/PMD-cameras suffer from systematic depth measurement errors which are modeled by a higher order function and are also estimated during the calibration process.

License:

This Software is an extension to the BIAS - Software - Library BIAS . This Software and BIAS are distributed in the hope that they will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU Lesser General Public License for more details.

To receive a copy of the GNU Lesser General Public License write to the Free Software Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA

Image Formats:

• For the intensity images most common file formats are supported. To name a few: mip, ppm, png, pgm, jpg.
• For the ToF images only two formats are supported. Our own mip-file format where the distance values are stored in mm. and a xml-file format which includes distance-values (in m!), greyscale values and amplitude values. (See "pmd0000.pmd (406.32 Kb)" for an example)

Note that if the xml-file format is used the files have to have the suffix ".pmd" to be loaded properly. Eventually you will have to give the image list with the pmd images two times in the properties GUI at the beginning. (As pmd-Intensity and pmd-Depth images.)

Download:

Go to the Download Page.

General Notes:

• What we calibrate: Intrinsic and extrinsic camera parameters (focal length, principle point, skew/shear, radial/tangential lens distortion, rotation and translation)
• The calibration approach is suitable for perspective and spherical (fisheye) cameras. The perspective case works very well and reliable, while the spherical case still has some known weaknesses. We use the method proposed by Scramuzza to approximate the parameters and try to refine them afterwards. In this refinement unfrequent crashes occur.
• The calibration algorithm is based on a planar checkerboard pattern. So if you want to calibrate your camera(s) you have to make pictures of a planar checkerboard pattern. The more pictures you make the more precise your result will be. It is also important that you cover all areas of your images with the calibration pattern. Especially the border regions of the images are mandatory if you want to have a precise result for radial and tangential lens distortion parameters. We typically use between 20 and 80 pictures per camera for calibration from different angles/ directions and distances.
• If you want to calibrate more than one camera you have to take the pictures of the checkerboard with all cameras at the same moment. Remember the cameras should be rigidly coupled! Again many images help to produce better results.
• If you want to calibrate a PMD-/ToF-/3D-camera and are interested in the depth error correction you have to take images of the calibration pattern at different distances. The distances should cover the whole operation area of the camera. Typical values are between 2.0m and 7.5m.
• The checkerboard has to be visible and detectable in your images, so ensure that it is big enough to be identified even in some distance to the cameras.
• The algorithm uses lists of images. The images have to be in the same order in the image lists. Images that are in the same position in the lists have to be taken simultaneously. The lists must have the same length. You can invalidate some images if, for example the checkerboard is not visible in that image. However you can't invalidate an image which belongs to the first camera in your rig, because the position and rotation of the other cameras is calculated relative to that first camera. (If you only want to calibrate one camera it is possible to invalidate pictures in this camera.)
  

Depth Error Model:

In the current version of the Software, the depth error is modelled as a polynomial:

where λ∗ is the corrected depth, x, y are the image coordinates, λ is the measured depth and di , i (0, ..., 5) are the parameters to estimate.

Besides the polynomial depth error model a spline model and linear error model are also implemented. The linear model consists only of an offset and an inclination parameter. The spline error model follows the proposed spline model introduced by Marvin Lindner and Andreas Kolb.

Marvin Lindner, Andreas Kolb
Lateral and Depth Calibration of PMD-Distance Sensors
In Advances in Visual Computing, Springer, 2, 2006, pages 524-533

You can choose which model to use in the project definition window.

Reference:

Further details can be found in the paper:

Configuration:

Starting the program will present a properties GUI where you can add the image lists and set some parameters.

• Add image lists to the calibration project. Image lists are just textfiles containing the paths of the image files. You can use the button on the bottom right corner to make image lists.
• When you add an image list you are asked if this is a spherical camera. This means if the FoV is ~180 degrees. In this case the software tries to estimate spline parameters after the model of Scaramuzza. If you use a standard perspective camera just press "No".
• After that you are asked if you want to fix the intrinsic parameters. This mean you can load the parameters such as principal point, focal length and lens distortion from file. Therefor the parameters have to be given in our file format. (Tip: Calibrate one camera without fixed parameters then you have a point to start)
• The depth distortion parameters are handled in a special way. If you load a file which includes depth parameters they are taken as fixed. If you load a file withour depth parameters or with all set to zero they are estimated. (Of course if you don't load anything they are estimated as well)
• Select the number of the inner corners of your checkerboard. For example this checkerboard:
  

has xCorners=7 and yCorners=4

• Select the size of one square of your checkerboard. That is for example the width of one single black rectangle in the image above.
• Select whether to use Software rendering or GPU rendering. The GPU rendering only works in NVIDIA cards Geforce 7950+. You can try it, but I recommend to use the software rendering, although it is slower.
• Choose which radial distortion model you wish to estimate, only the radial distortion parameters (Bouguet), radial and tangential distortion parameters or distortion parameters as Brown defined them (still experimental).
• Select which depth error model you wish to use. Polynomial, Linear or Spline (still experimental).
• Finally select whether your checkerboard is black or white in the top left corner.

Save you project before pressing ok or you will have to configure it again!

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