--- title: Standard Camera Calibrations slug: api-guide/standard-camera-calibrations docTags: createdAt: 2024-12-17T10:17:00.508Z --- The Camera calibration format is based on [OpenCVs](https://docs.opencv.org/3.4/d4/d94/tutorial_camera_calibration.html) format and this [paper](http://www.robots.ox.ac.uk/~cmei/articles/single_viewpoint_calib_mei_07.pdf). The different camera types supported are: `PINHOLE`, `FISHEYE`, `KANNALA`, `PRINCIPALPOINTDIST`, and `FUSEDCYLINDRICAL`. If your calibration model is not supported, you can also provide a [Custom Camera Calibrations](docId\:F_jarCzytV6CXwZc675zK) where you provide the implementation in the form of a WebAssembly module. ![](https://api.archbee.com/api/optimize/wLEz_RbWP6nIMpY-prjlm/YTQ9f_IgNoIxDhdwxUqcr_camera-calibration.jpg) ### Common All camera calibrations have the following attributes | Key | Value | Parameters | | --------------------- | ----------------------------- | ---------------------- | | `rotation_quaternion` | A `RotationQuaternion` object | `w`, `x`, `y`, `z` | | `position` | A `Position` object | `x`, `y`, `z` | | `camera_matrix` | A `CameraMatrix` object | `fx`, `fy`, `cx`, `cy` | | `image_width` | Integer | NA | | `image_height` | Integer | NA | | `field_of_view` | Float | NA | ### Pinhole The `PINHOLE` camera model expands the common model with: | Key | Value | Parameters | | ------------------------- | --------------------------------- | ---------------------------- | | `distortion_coefficients` | A `DistortionCoefficients` object | `k1`, `k2`, `p1`, `p2`, `k3` | ```python from kognic.io.model.calibration.camera.common import CameraMatrix, DistortionCoefficients from kognic.io.model.calibration.camera.pinhole_calibration import PinholeCalibration from kognic.io.model.calibration.common import Position, RotationQuaternion def unity_pinhole_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=3450, fy=3250, cx=622, cy=400) camera_distortion_coefficients = DistortionCoefficients(k1=0.0, k2=0.0, p1=0.0, p2=0.0, k3=1.0) return PinholeCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, distortion_coefficients=camera_distortion_coefficients, image_height=1080, image_width=1920, field_of_view=190.0, ) ``` ### Fisheye The Fisheye camera model expands the `PINHOLE` model with the following | Key | Value | Parameters | | ---- | ----- | ---------- | | `xi` | Float | NA | ```python from kognic.io.model.calibration.camera.common import CameraMatrix, DistortionCoefficients from kognic.io.model.calibration.camera.fisheye_calibration import FisheyeCalibration from kognic.io.model.calibration.common import Position, RotationQuaternion def unity_fisheye_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=3450, fy=3250, cx=622, cy=400) camera_distortion_coefficients = DistortionCoefficients(k1=0.0, k2=0.0, p1=0.0, p2=0.0, k3=0.1) return FisheyeCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, distortion_coefficients=camera_distortion_coefficients, image_height=1080, image_width=1920, xi=123.456, field_of_view=190.0, ) ``` ### Kannala The `KANNALA` camera model changes and expands the `PINHOLE` with the following | Key | Value | Parameters | | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------- | | `distortion_coefficients` | A `KannalaDistortionCoefficients` object. The distortion parameters `k3`, `k4`, if available, can be assigned to `p1` and `p2` respectively. That is `p1=k3` and `p2=k4`. | `k1`, `k2`, `p1`, `p2` | | `undistortion_coefficients` | A `UndistortionCoefficients` object. | `l1`, `l2`, `l3`, `l4` | ```python from kognic.io.model.calibration.camera.common import CameraMatrix from kognic.io.model.calibration.camera.kannala_calibration import ( KannalaCalibration, KannalaDistortionCoefficients, UndistortionCoefficients, ) from kognic.io.model.calibration.common import Position, RotationQuaternion def unity_kannala_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) # similar to Lidar camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) # similar to Lidar camera_camera_matrix = CameraMatrix(fx=3450, fy=3250, cx=622, cy=400) camera_distortion_coefficients = KannalaDistortionCoefficients(k1=0.0, k2=0.0, p1=0.0, p2=0.0) camera_undistortion_coefficients = UndistortionCoefficients(l1=0.0, l2=0.0, l3=0.0, l4=0.0) return KannalaCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, distortion_coefficients=camera_distortion_coefficients, undistortion_coefficients=camera_undistortion_coefficients, image_height=1080, image_width=1920, field_of_view=180.0, ) ``` ### Principal point distortion The principal point distortion model consists of the common attributes plus | Key | Value | Parameters | | ---------------------------------------------------------------------------- | ----------------------------------------------- | -------------------------------- | | `principal_point_distortion_coefficients` | A `PrincipalPointDistortionCoefficients` object | `k1`, `k2` | | `lens_projection_coefficients` (optional. Default to values for model SF806) | A `LensProjectionCoefficients` object | `c1`, `c2`,`c3`, `c4`,`c5`, `c6` | | `distortion_center` | A `DistortionCenter` object | `x`, `y` | | `principal_point` | A `PrincipalPoint` object | `x`, `y` | ```python from kognic.io.model.calibration.camera.common import CameraMatrix from kognic.io.model.calibration.camera.principal_point_distortion_calibration import ( DistortionCenter, LensProjectionCoefficients, PrincipalPoint, PrincipalPointDistortionCalibration, PrincipalPointDistortionCoefficients, ) from kognic.io.model.calibration.common import Position, RotationQuaternion def unity_principal_point_distortion_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=3450, fy=3250, cx=622, cy=400) camera_distortion_coefficients = PrincipalPointDistortionCoefficients(k1=0.0, k2=0.0) principal_point = PrincipalPoint(x=0.0, y=0.0) distortion_center = DistortionCenter(x=0.0, y=0.0) lens_projection_coefficients = LensProjectionCoefficients(c1=0.0, c2=0.0, c3=0.0, c4=0.0, c5=0.0, c6=0.0) return PrincipalPointDistortionCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, principal_point_distortion_coefficients=camera_distortion_coefficients, lens_projection_coefficients=lens_projection_coefficients, principal_point=principal_point, distortion_center=distortion_center, image_height=1080, image_width=1920, field_of_view=180.0, ) ``` ### Fused cylindrical The fused cylindrical model consists of the common attributes plus | Key | Value | Parameters | | ---------------------------------------------------------- | ----------------------------------------------------------------------- | ---------------- | | `cut_angles_degree` | A `CutAngles` object. Note these angles should be expressed in degrees. | `upper`, `lower` | | `vertical_fov_degree` (optional. Default 72.5 degrees) | Float. Note this angle should be expressed in degrees. | NA | | `horizontal_fov_degree` (optional. Default 93 degrees) | Float. Note this angle should be expressed in degrees. | NA | | `max_altitude_angle_degree` (optional. Default 90 degrees) | Float. Note this angle should be expressed in degrees. | NA | ```python from kognic.io.model.calibration.camera.common import CameraMatrix from kognic.io.model.calibration.camera.fused_cylindrical_calibration import CutAngles, FusedCylindricalCalibration from kognic.io.model.calibration.common import Position, RotationQuaternion def example_fused_cylindrical_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=400, fy=400, cx=600, cy=450) cut_angles_degree = CutAngles(upper=-40.0, lower=30.0) return FusedCylindricalCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, image_height=1080, image_width=1920, cut_angles_degree=cut_angles_degree, vertical_fov_degree=70, horizontal_fov_degree=90.0, max_altitude_angle_degree=90.0, ) ``` ### Cylindrical The cylindrical model consists only of the common attributes. There are no extra attributes to set for this model. ```python from kognic.io.model.calibration.camera.common import CameraMatrix from kognic.io.model.calibration.camera.cylindrical_calibration import CylindricalCalibration from kognic.io.model.calibration.common import Position, RotationQuaternion def example_cylindrical_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=400, fy=400, cx=600, cy=450) return CylindricalCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, image_height=1080, image_width=1920, ) ``` ### Principal point fisheye The principal point fisheye model consists of the common attributes plus | Key | Value | Parameters | | -------------------------------------- | -------------------------------------------- | ---------------------------------------- | | `principal_point_fisheye_coefficients` | A `PrincipalPointFisheyeCoefficients` object | `alpha_l`, `alpha_r`, `beta_u`, `beta_l` | ```python from kognic.io.model.calibration.camera.common import CameraMatrix from kognic.io.model.calibration.camera.principal_point_fisheye_calibration import ( PrincipalPointFisheyeCalibration, PrincipalPointFisheyeCoefficients, ) from kognic.io.model.calibration.common import Position, RotationQuaternion def unity_principal_point_fisheye_calibration(): camera_position = Position(x=0.0, y=0.0, z=0.0) camera_rotation = RotationQuaternion(w=1.0, x=0.0, y=0.0, z=0.0) camera_camera_matrix = CameraMatrix(fx=3450, fy=3250, cx=622, cy=400) principal_point_fisheye_coefficients = PrincipalPointFisheyeCoefficients(alpha_l=0.0, alpha_r=0.0, beta_u=0.0, beta_l=0.0) return PrincipalPointFisheyeCalibration( position=camera_position, rotation_quaternion=camera_rotation, camera_matrix=camera_camera_matrix, principal_point_fisheye_coefficients=principal_point_fisheye_coefficients, image_height=1080, image_width=1920, field_of_view=180.0, ) ```