cameraParameters
Object for storing camera parameters
Description
The cameraParameters
object stores the intrinsic,
extrinsic, and lens distortion parameters of a camera.
Creation
You can create a cameraParameters
object using the
cameraParameters
function described here. You can also create a
cameraParameters
object by using the estimateCameraParameters
with an
M-by-2-by-numImages array of input image
points. M is the number of keypoint coordinates in each
pattern.
Syntax
Description
creates a cameraParams
= cameraParameterscameraParameters
object that contains the
intrinsic, extrinsic, and lens distortion parameters of a camera.
sets properties of
the cameraParams
= cameraParameters(Name,Value)cameraParameters
object by using one or more
Name,Value
pair arguments. Unspecified properties use
default values.
creates an identical cameraParams
= cameraParameters(paramStruct
)cameraParameters
object from an existing
cameraParameters
object with parameters stored in
paramStruct
.
Input Arguments
paramStruct
— Camera parameters
struct
Stereo parameters, specified as a stereo parameters struct. To get a
paramStruct
from an existing
cameraParameters
object, use the toStruct
function.
Properties
Intrinsic Camera Parameters:
IntrinsicMatrix
— Projection matrix
3-by-3 identity matrix
Projection matrix, specified as a 3-by-3 identity matrix. The object uses the following format for the matrix format:
The coordinates
[cx
cy] represent the optical center
(the principal point), in pixels. When the x and
y axis are exactly perpendicular, the skew parameter,
s, equals 0
.
fx = F*sx |
fy = F*sy |
F, is the focal length in world units, typically expressed in millimeters. |
[sx, sy] are the number of pixels per world unit in the x and y direction respectively. |
fx and fy are expressed in pixels. |
Intrinsics
— Camera intrinsics object
cameraIntrinsics
object
This property is read-only.
Camera intrinsics object, stated as a cameraIntrinsics
object. The
object contains information about camera intrinsic calibration parameters,
including lens distortion.
Dependency
You must provide an image size (using the
ImageSize
property) for the
Intrinsics
property to be non-empty. The
intrinsics for the camera parameters depends on the image size.
ImageSize
— Image size
two-element vector
Image size, specified as a two-element vector [mrows,ncols].
Camera Lens Distortion:
RadialDistortion
— Radial distortion coefficients
[0 0 0]
(default) | 2-element vector | 3-element vector
Radial distortion coefficients, specified as either a two- or
three-element vector. When you specify a two-element vector, the object sets
the third element to 0
. Radial distortion is the
displacement of image points along radial lines extending from the principal
point.
The camera parameters object calculates the radial-distorted location of a point. You can denote the distorted points as (xdistorted, ydistorted), as follows:
xdistorted = x(1 + k1*r2 + k2*r4 + k3*r6) | (1) |
ydistorted= y(1 + k1*r2 + k2*r4 + k3*r6) | (2) |
x, y = undistorted pixel locations |
k1, k2, and k3 = radial distortion coefficients of the lens |
r2 = x2 + y2 |
TangentialDistortion
— Tangential distortion coefficients
[0 0]'
(default) | 2-element vector
Tangential distortion coefficients, specified as a two-element vector. Tangential distortion occurs when the lens and the image plane are not parallel. The camera parameters object calculates the tangential distorted location of a point. You can denote the distorted points as (xdistorted, ydistorted). The undistorted pixel locations appear in normalized image coordinates, with the origin at the optical center. The coordinates are expressed in world units.
Tangential distortion occurs when the lens and the image plane are not parallel. The tangential distortion coefficients model this type of distortion.
The distorted points are denoted as (xdistorted, ydistorted):
xdistorted = x + [2 * p1 * x * y + p2 * (r2 + 2 * x2)]
ydistorted = y + [p1 * (r2 + 2 *y2) + 2 * p2 * x * y]
x, y — Undistorted pixel locations. x and y are in normalized image coordinates. Normalized image coordinates are calculated from pixel coordinates by translating to the optical center and dividing by the focal length in pixels. Thus, x and y are dimensionless.
p1 and p2 — Tangential distortion coefficients of the lens.
r2 = x2 + y2
Extrinsic Camera Parameters:
RotationMatrices
— 3-D rotation matrix
3-by-3-by-P matrix (read-only)
3-D rotation matrix, specified as a 3-by-3-by-P, with P number of pattern images. Each 3-by-3 matrix represents the same 3-D rotation as the corresponding vector.
The following equation provides the transformation that relates a world coordinate in the checkerboard frame [X Y Z] and the corresponding image point [x y]:
R is the 3-D rotation matrix. |
t is the translation vector. |
K is the
IntrinsicMatrix . |
s is a scalar. |
undistortImage
function
removes distortion.
RotationVectors
— 3-D rotation vectors
[]
(default) | P-by-3 matrix (read-only)
3-D rotation vectors, specified as a P-by-3 matrix
containing P rotation vectors. Each vector describes the
3-D rotation of the camera image plane relative to the corresponding
calibration pattern. The vector specifies the 3-D axis about which the
camera is rotated, where the magnitude is the rotation angle in radians. The
RotationMatrices
property provides the
corresponding 3-D rotation matrices.
TranslationVectors
— Camera translations
[]
(default) | P-by-3 matrix
Camera translations, specified as an P-by-3 matrix. This matrix contains translation vectors for P images. The vectors contain the calibration pattern that estimates the calibration parameters. Each row of the matrix contains a vector that describes the translation of the camera relative to the corresponding pattern, expressed in world units.
The following equation provides the transformation that relates a world coordinate in the checkerboard frame [X Y Z] and the corresponding image point [x y]:
R is the 3-D rotation matrix. |
t is the translation vector. |
K is the
IntrinsicMatrix . |
s is a scalar. |
undistortImage
function
removes distortion.
To ensure that the number of rotation vectors equals the number of
translation vectors, set the RotationVectors
and
TranslationVectors
properties in the constructor.
Setting only one property but not the other results in an error.
Estimated Camera Parameter Accuracy:
MeanReprojectionError
— Average Euclidean distance
numeric value (read-only)
Average Euclidean distance between reprojected and detected points, specified as a numeric value in pixels.
ReprojectionErrors
— Estimated camera parameters accuracy
[]
(default) | M-by-2-by-P array
Estimated camera parameters accuracy, specified as an M-by-2-by-P array of [x y] coordinates. The [x y] coordinates represent the translation in x and y between the reprojected pattern key points and the detected pattern key points. The values of this property represent the accuracy of the estimated camera parameters. P is the number of pattern images that estimates camera parameters. M is the number of keypoints in each image.
ReprojectedPoints
— World points reprojected onto calibration images
M-by-2-by-P array
World points reprojected onto calibration images, specified as an
M-by-2-by-P array of
[x
y] coordinates. P is the number of
pattern images and M is the number of keypoints in each
image. Missing points in the pattern's detected keypoints are denoted as
[NaN,NaN
].
DetectedKeypoints
— Detected keypoints in the calibration pattern
[]
(default) | M-by-P array
Detected keypoints in the calibration pattern, specified as a logical M-by-P array. M is the number of keypoints in the entire calibration pattern and P specifies the number of calibration images.
Settings for Camera Parameter Estimation:
NumPatterns
— Number of calibrated patterns
integer
Number of calibration patterns that estimates camera extrinsics, specified as an integer. The number of calibration patterns equals the number of translation and rotation vectors.
WorldPoints
— World coordinates
M-by-2 array | []
World coordinates of key points on calibration pattern, specified as an M-by-2 array. M represents the number of key points in the pattern.
WorldUnits
— World points units
'mm'
(default) | character vector | string scalar
World points units, specified as a character vector or string scalar. The value describes the units of measure.
EstimateSkew
— Estimate skew flag
false
(default) | logical scalar
Estimate skew flag, specified as a logical scalar. When you set the
logical to true
, the object estimates the image axes
skew. When you set the logical to false
, the image axes
are exactly perpendicular.
NumRadialDistortionCoefficients
— Number of radial distortion coefficients
2
(default) | 3
Number of radial distortion coefficients, specified as the number
'2
' or '3
'.
EstimateTangentialDistortion
— Estimate tangential distortion flag
false
(default) | logical scalar
Estimate tangential distortion flag, specified as the logical scalar
true
or false
. When you set the
logical to true
, the object estimates the tangential
distortion. When you set the logical to false
, the
tangential distortion is negligible.
Examples
Remove Distortion from an Image Using the Camera Parameters Object
Use the camera calibration functions to remove distortion from an image. This example creates a vision.cameraParameters
object manually, but in practice, you would use the estimateCameraParameters
or the Camera Calibrator app to derive the object.
Create a vision.cameraParameters
object manually.
IntrinsicMatrix = [715.2699 0 0; 0 711.5281 0; 565.6995 355.3466 1]; radialDistortion = [-0.3361 0.0921]; cameraParams = cameraParameters('IntrinsicMatrix',IntrinsicMatrix,'RadialDistortion',radialDistortion);
Remove distortion from the images.
I = imread(fullfile(matlabroot,'toolbox','vision','visiondata','calibration','mono','image01.jpg')); J = undistortImage(I,cameraParams);
Display the original and the undistorted images.
figure; imshowpair(imresize(I,0.5),imresize(J,0.5),'montage'); title('Original Image (left) vs. Corrected Image (right)');
References
[1] Zhang, Z. “A flexible new technique for camera calibration”. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 11, pp. 1330–1334, 2000.
[2] Heikkila, J, and O. Silven. “A Four-step Camera Calibration Procedure with Implicit Image Correction”, IEEE International Conference on Computer Vision and Pattern Recognition, 1997.
Extended Capabilities
C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.
Usage notes and limitations:
Use the
toStruct
method to pass acameraParameters
object into generated code. See the Code Generation for Depth Estimation From Stereo Video example.
Version History
See Also
Apps
Classes
stereoParameters
|cameraCalibrationErrors
|intrinsicsEstimationErrors
|extrinsicsEstimationErrors
|cameraIntrinsics
Functions
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