File prior_factor_linear_camera_cal.h

namespace sym

Functions

template<typename Scalar>
void PriorFactorLinearCameraCal(const sym::LinearCameraCal<Scalar> &value, const sym::LinearCameraCal<Scalar> &prior, const Eigen::Matrix<Scalar, 4, 4> &sqrt_info, const Scalar epsilon, Eigen::Matrix<Scalar, 4, 1> *const res = nullptr, Eigen::Matrix<Scalar, 4, 4> *const jacobian = nullptr, Eigen::Matrix<Scalar, 4, 4> *const hessian = nullptr, Eigen::Matrix<Scalar, 4, 1> *const rhs = nullptr)

Residual that penalizes the difference between a value and prior (desired / measured value).

In vector space terms that would be: prior - value

In lie group terms: to_tangent(compose(inverse(value), prior))

Args: sqrt_info: Square root information matrix to whiten residual. This can be computed from a covariance matrix as the cholesky decomposition of the inverse. In the case of a diagonal it will contain 1/sigma values. Must match the tangent dim. jacobian: (4x4) jacobian of res wrt arg value (4) hessian: (4x4) Gauss-Newton hessian for arg value (4) rhs: (4x1) Gauss-Newton rhs for arg value (4)