Camera models and calibration

Camera models

A set of classes that model the projective geometry of cameras.

CentralCamera	Create central camera projection model
FishEyeCamera	Create fisheye camera projection model
CatadioptricCamera	Create catadioptric camera projection model
SphericalCamera	Create spherical camera projection model

Calibration

Intrinsic calibration of camera from multiple images

class CentralCamera(f: float | int | list[float | int] | tuple[float | int, ...] | ndarray = 1, distortion: ndarray | None = None, **kwargs)

Create central camera projection model

Parameters:

• f (float, optional) – focal length, defaults to 8mm

• distortion (array_like(5), optional) – camera distortion parameters, defaults to None

• kwargs – arguments passed to CameraBase constructor

A camera object contains methods for projecting 3D points and lines to the image plane, as well as supporting a virtual image plane onto which 3D points and lines can be drawn.

References:

• P. Corke, Robotics, Vision & Control for Python, Springer, 2023, Section 13.1.

Seealso:

CameraBase FishEyeCamera SphericalCamera

classmethod images2C(images, gridshape: tuple[int, int] = (7, 6), squaresize: float = 0.025) → tuple[ndarray, ndarray, list] | None

Calibrate camera from checkerboard images

Parameters:

• images (ImageSource) – an iterator that returns Image objects

• gridshape (tuple, optional) – number of grid squares in each dimension, defaults to (7,6)

• squaresize (float, optional) – size of the grid squares in units of length, defaults to 0.025

Returns:

camera calibration matrix, distortion parameters, image frames

Return type:

ndarray(3,4), ndarray(5), list of named tuples

The distortion coefficients are in the order \((k_1, k_2, p_1, p_2, k_3)\) where \(k_i\) are radial distortion coefficients and \(p_i\) are tangential distortion coefficients.

Image frames that were successfully processed are returned as a list of named tuples CalibrationFrame with elements:

element	type	description
image	Image	calibration image with overlaid annotation
pose	SE3 instance	pose of the camera with respect to the origin of this image
id	int	sequence number of this image in images

Note

The units used for squaresize must match the units used for defining 3D points in space.

References:

• P. Corke, Robotics, Vision & Control for Python, Springer, 2023, Section 13.7.

Seealso:

C points2C decomposeC SE3