List of Operators ↓

This chapter describes how to calibrate different multi-view camera setups.

In order to achieve high accuracy for your measuring tasks you need to calibrate your camera setup. In comparison to a single-camera setup, some additional requirements apply to the calibration of a multi-view camera setup. The following paragraphs provide explanations regarding the calibration of multi-view camera setups. For general information on camera calibration please refer to the chapter reference Calibration.

Preparing the Calibration Input Data for Multi-View Camera Setups

Before the actual calibration can be performed, a calibration data model must be prepared (as described in Calibration). For setups with multiple cameras, these additional aspects should be considered:

Performing the Actual Camera Calibration

The calibration performed by calibrate_camerascalibrate_camerasCalibrateCamerasCalibrateCamerasCalibrateCameras depends on the camera types that are involved in the calibration setup. While different camera setups require specific conditions when acquiring images, the basic steps of the calibration procedure for setups including projective and/or telecentric cameras are similar:

  1. Building a chain of observation poses: In the first step, the operator calibrate_camerascalibrate_camerasCalibrateCamerasCalibrateCamerasCalibrateCameras tries to build a valid chain of observation poses, that connects all cameras and calibration object poses to the reference camera. Depending on the setup, the conditions for a valid chain of poses differ. For specific information see the respective paragraphs below.

    If there is a camera that cannot be reached (i.e., it is not observing any calibration object pose that can be connected in the chain), the calibration process is terminated with an error. Otherwise, the algorithm initializes all calibration items' poses by going down this chain.

  2. First optimization: In this step, calibrate_camerascalibrate_camerasCalibrateCamerasCalibrateCamerasCalibrateCameras performs the actual optimization for all optimization parameters that were not explicitly excluded from the calibration.

  3. Second optimization: Based on the so-far calibrated cameras, the algorithm corrects all observations that contain mark contour information (see find_calib_objectfind_calib_objectFindCalibObjectFindCalibObjectFindCalibObject). Then, the calibration setup is optimized anew for the corrections to take effect. If no contour information was available, this step is skipped.

  4. Compute quality of parameter estimation: In the last step, calibrate_camerascalibrate_camerasCalibrateCamerasCalibrateCamerasCalibrateCameras computes the standard deviations and the covariances of the calibrated internal camera parameters.

The following paragraphs give further information about the conditions specific to the camera setups.

Projective area scan cameras

For a setup with projective area scan cameras, the calibration is performed in the four steps listed above. The algorithm tries to build a chain of observation poses that connects all cameras and calibration object poses to the reference camera like in the diagram below.

image/svg+xml image/svg+xml
(1) (2)
(1) All cameras can be connected by a chain of observation poses. (2) The leftmost camera is isolated, because the left calibration plate cannot be seen by any other camera.

Possible projective area scan cameras are:

Telecentric area-scan cameras

For a setup with telecentric area-scan cameras, similar to projective area scan cameras, the same four steps that are listed above are executed. In the first step (building a chain of observation poses that connects all cameras and calibration objects), additional conditions must hold. Since the pose of an object can only be determined up to a translation along the optical axis, each calibration object must be observed by at least two cameras to determine its relative location. Otherwise, its pose is excluded from the calibration. Also, since a planar calibration object appears the same from two different observation angles, the relative pose of the cameras among each other cannot be determined unambiguously. Therefore, there are always two valid alternative relative poses. Both alternatives result in a consistent camera setup which can be used for measuring. Since the ambiguity cannot be resolved, the first of the alternatives is returned. Note that, if the returned pose is not the real pose but the alternative one, then this will result in a mirrored reconstruction.

Possible telecentric area scan cameras are:

Projective and telecentric area scan cameras

For a mixed setup with projective and telecentric area scan cameras, the algorithm performs the same four steps as enumerated above. Possible ambiguities during the first step (building a chain of observation poses that connects all cameras and calibration objects), as described above for the setup with telecentric cameras, can be resolved as long as there exists a chain of observation poses consisting of all perspective cameras and a sufficient number of calibration objects. Here, sufficient number means that each telecentric camera observes at least two calibration objects of this chain.

image/svg+xml (P) (T) (P) image/svg+xml (P) (T) (P)
(1) (2)
Mixed calibration setup with perspective (P) and telecentric (T) area scan cameras. (1) All perspective cameras are connected by a chain of observation poses that only contains perspective cameras. (2) The second calibration plate (from the left) is not observed by the rightmost perspective camera. Therefore, the relative pose between both perspective cameras cannot be determined uniquely.
Line scan cameras

For a setup with line scan cameras ('line_scan'"line_scan""line_scan""line_scan""line_scan" and 'line_scan_telecentric'"line_scan_telecentric""line_scan_telecentric""line_scan_telecentric""line_scan_telecentric"), the following restriction exists: only one camera can be calibrated and only one calibration object per setup can be used.

Finally, for calibration plates with rectangularly arranged marks (see gen_caltabgen_caltabGenCaltabGenCaltabGenCaltab) all observations must contain the projection coordinates of all calibration marks of the calibration object. For calibration plates with hexagonally arranged marks (see create_caltabcreate_caltabCreateCaltabCreateCaltabCreateCaltab) this restriction is not applied. You can find further information about calibration plates and the acquisition of calibration images in the section “Additional information about the calibration process” within the chapter Calibration.

Checking the Success of the Calibration

If more than one camera is calibrated simultaneously, the value of ErrorErrorErrorErrorerror is more difficult to judge. As a rule of thumb, ErrorErrorErrorErrorerror should be as small as possible and at least smaller than 1.0, thus indicating that a subpixel precise evaluation of the data is possible with the calibrated parameters. This value might be difficult to reach in particular configurations. For further analysis of the quality of the calibration, refer to the standard deviations and covariances of the estimated parameters.

Getting the Calibration Results

The results of the calibration, i.e., internal camera parameters, camera poses (external camera parameters), calibration objects poses etc., can be queried with get_calib_dataget_calib_dataGetCalibDataGetCalibDataGetCalibData.

Note that the poses of telecentric cameras can only be determined up to a displacement along the z-axis of the coordinate system of the respective camera (perpendicular to the image plane). Therefore, all camera poses are moved along this axis until they all lie on a common sphere. The center of the sphere is defined by the pose of the first calibration object. The radius of the sphere depends on the calibration setup. If projective and telecentric area scan cameras are calibrated, the radius is the maximum over all distances from the perspective cameras to the first calibration object. Otherwise, if only telecentric area scan cameras are considered, the radius is equal to 1 m.

List of Operators

Determine all camera parameters by a simultaneous minimization process.
Free the memory of a calibration data model.
Free the memory of a calibration setup model.
Create a HALCON calibration data model.
Create a model for a setup of calibrated cameras.
Deserialize a serialized calibration data model.
Deserialize a serialized camera setup model.
Query data stored or computed in a calibration data model.
Get contour-based observation data from a calibration data model.
Get point-based observation data from a calibration data model.
Get generic camera setup model parameters.
Query information about the relations between cameras, calibration objects, and calibration object poses.
Restore a calibration data model from a file.
Restore a camera setup model from a file.
Remove a data set from a calibration data model.
Remove observation data from a calibration data model.
Serialize a calibration data model.
Serialize a camera setup model.
Set data in a calibration data model.
Define a calibration object in a calibration model.
Set type and initial parameters of a camera in a calibration data model.
Set point-based observation data in a calibration data model.
Define type, parameters, and relative pose of a camera in a camera setup model.
Set generic camera setup model parameters.
Store a calibration data model into a file.
Store a camera setup model into a file.