Operator Reference
Multi-View
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 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:
-
The number of cameras in the setup and the number of used calibration objects can be set when calling
.create_calib_data
-
When specifying the camera type with
, note that only cameras of the same type (i.e., area scan or line scan) can be calibrated in a single setup.set_calib_data_cam_param
-
Configure the calibration process, e.g., specify the reference camera, using
. You can also specify parameters for the complete setup or just configure parameters of individual cameras as well as calibration object poses in the setup.set_calib_data
Performing the Actual Camera Calibration
The calibration performed by
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:
calibrate_cameras
-
Building a chain of observation poses: In the first step, the operator
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.calibrate_cameras
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.
-
First optimization: In this step,
performs the actual optimization for all optimization parameters that were not explicitly excluded from the calibration.calibrate_cameras
-
Second optimization: Based on the so-far calibrated cameras, the algorithm corrects all observations that contain mark contour information (see
). Then, the calibration setup is optimized anew for the corrections to take effect. If no contour information was available, this step is skipped.find_calib_object
-
Compute quality of parameter estimation: In the last step,
computes the standard deviations and the covariances of the calibrated internal camera parameters.calibrate_cameras
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.
( 1) ( 2) Possible projective area scan cameras are:
-
'area_scan_division'
-
'area_scan_polynomial'
-
'area_scan_tilt_division'
-
'area_scan_tilt_polynomial'
-
'area_scan_tilt_image_side_telecentric_division'
-
'area_scan_tilt_image_side_telecentric_polynomial'
-
'area_scan_hypercentric_division'
-
'area_scan_hypercentric_polynomial'
-
- 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:
-
'area_scan_telecentric_division'
-
'area_scan_telecentric_polynomial'
-
'area_scan_tilt_bilateral_telecentric_division'
-
'area_scan_tilt_bilateral_telecentric_polynomial'
-
'area_scan_tilt_object_side_telecentric_division'
-
'area_scan_tilt_object_side_telecentric_polynomial'
-
- 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.
( 1) ( 2) - Line scan cameras
-
Setups with telecentric line scan cameras (
'line_scan_telecentric'
) behave identically to setups with telecentric area scan cameras and the same restrictions and ambiguities that are described above apply. For this type of setup, two possible configurations can be distinguished. In the first configuration, all cameras are mounted rigidly and stationary and the object is moved linearly in front of the cameras. Alternatively, all cameras are mounted rigidly with respect to each other and are moved across the object by the same linear actuator. In both cases, all cameras share a common motion vector, which is modeled in the camera coordinate system of the reference camera and is transformed to the camera coordinate systems of all other cameras by the rotation part of the respective camera's pose. This configuration is assumed by default. In the second configuration, the cameras are moved by independent linear actuators in different directions. In this case, each camera has its own independent motion vector. The type of configuration can be selected with
.set_calib_data
( 1) ( 2) ( 3) Note that two different stereo setups are common for telecentric line scan cameras. For both setups, a linear, constant motion is assumed for the observed object or the camera system respectively.
-
For along-track setups one camera is placed in front, looking in backwards direction, while the second camera is mounted behind, looking forwards, both at an suitable angle in respect to the motion vector.
-
The cameras in an across-track setup are all directed perpendicular to the motion vector, while the viewing planes are approximately coplanar. Therefore, the depth of field is rather limited. Precise measurements are only possible in areas where the depth of field of the individual cameras overlap.
( 1) ( 2) For setups with projective line scan cameras (
'line_scan'
), 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
) all observations must contain the projection
coordinates of all calibration marks of the calibration object. For
calibration plates with hexagonally arranged marks (see
gen_caltab
) 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.
create_caltab
Checking the Success of the Calibration
If more than one camera is calibrated simultaneously, the value
of
is more difficult to judge.
As a rule of thumb, Error
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.
Error
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_data
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.
Further Information
Learn about the calibration of multi-camera setups and many other topics in interactive online courses at our MVTec Academy .
List of Operators
calibrate_cameras
- Determine all camera parameters by a simultaneous minimization process.
clear_calib_data
- Free the memory of a calibration data model.
clear_camera_setup_model
- Free the memory of a calibration setup model.
create_calib_data
- Create a HALCON calibration data model.
create_camera_setup_model
- Create a model for a setup of calibrated cameras.
deserialize_calib_data
- Deserialize a serialized calibration data model.
deserialize_camera_setup_model
- Deserialize a serialized camera setup model.
get_calib_data
- Query data stored or computed in a calibration data model.
get_calib_data_observ_contours
- Get contour-based observation data from a calibration data model.
get_calib_data_observ_points
- Get point-based observation data from a calibration data model.
get_camera_setup_param
- Get generic camera setup model parameters.
query_calib_data_observ_indices
- Query information about the relations between cameras, calibration objects, and calibration object poses.
read_calib_data
- Restore a calibration data model from a file.
read_camera_setup_model
- Restore a camera setup model from a file.
remove_calib_data
- Remove a data set from a calibration data model.
remove_calib_data_observ
- Remove observation data from a calibration data model.
serialize_calib_data
- Serialize a calibration data model.
serialize_camera_setup_model
- Serialize a camera setup model.
set_calib_data
- Set data in a calibration data model.
set_calib_data_calib_object
- Define a calibration object in a calibration model.
set_calib_data_cam_param
- Set type and initial parameters of a camera in a calibration data model.
set_calib_data_observ_points
- Set point-based observation data in a calibration data model.
set_camera_setup_cam_param
- Define type, parameters, and relative pose of a camera in a camera setup model.
set_camera_setup_param
- Set generic camera setup model parameters.
write_calib_data
- Store a calibration data model into a file.
write_camera_setup_model
- Store a camera setup model into a file.