The most common 5DOF 3D->2D calibration. More...

The most common 5DOF 3D->2D calibration.

A 2D stereo point, v will be same for rectified images.

A stereo camera class, parameterize by left camera pose and stereo calibration.

A 3D rotation represented as a rotation matrix if the preprocessor symbol GTSAM_USE_QUATERNIONS is not defined, or as a quaternion if it is defined.

Rotation matrix NOTE: the angle theta is in radians unless explicitly stated.

A 3D pose (R,t) : (Rot3,Point3)

A 2D pose (Point2,Rot2)

A 3D point.

A 2D point Complies with the Testable Concept Functional, so no set functions: once created, a point is constant.

A pinhole camera class that has a Pose3 and a Calibration.

A Calibrated camera class [R|-R't], calibration K=I.

Calibration of a omni-directional camera with mirror + lens radial distortion.

Calibration of a camera with radial distortion.

Calibration used by Bundler.

The most common 5DOF 3D->2D calibration, stereo version.

Uses same distortionmodel as OpenCV, with http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html but using only k1,k2,p1, and p2 coefficients. K = [ fx s u0 ; 0 fy v0 ; 0 0 1 ] rr = Pn.x^2 + Pn.y^2 {pn} = (1 + k1*rr + k2*rr^2 ) pn + [ 2*k3 pn.x pn.y + k4 (rr + 2 Pn.x^2) ; k3 (rr + 2 Pn.y^2) + 2*k4 pn.x pn.y ] pi = K*pn

Similar to Cal3DS2, does distortion but has additional mirror parameter xi K = [ fx s u0 ; 0 fy v0 ; 0 0 1 ] Pn = [ P.x / (1 + xi * {P.x^2 + P.y^2 + 1}), P.y / (1 + xi * {P.x^2 + P.y^2 + 1})] rr = Pn.x^2 + Pn.y^2 {pn} = (1 + k1*rr + k2*rr^2 ) pn + [ 2*k3 pn.x pn.y + k4 (rr + 2 Pn.x^2) ; k3 (rr + 2 Pn.y^2) + 2*k4 pn.x pn.y ] pi = K*pn

If calibration is known, it is more computationally efficient to calibrate the measurements rather than try to predict in pixels.