:math:`E` is an essential matrix,
:math:`p_1` and
:math:`p_2` are corresponding points in the first and the second images, respectively.
-The result of this function may be passed further to ``decomposeEssentialMat()`` or ``recoverPose()`` to recover the relative pose between cameras.
+The result of this function may be passed further to :ocv:func:`decomposeEssentialMat` or :ocv:func:`recoverPose` to recover the relative pose between cameras.
decomposeEssentialMat
-------------------------
Only these inliers will be used to recover pose.
In the output mask only inliers which pass the cheirality check.
-This function decomposes an essential matrix using ``decomposeEssentialMat()`` and then verifies possible pose hypotheses by doing cheirality check.
-The cheirality check basically means that the triangulated 3D points should have positive depth. Some details can be found from [Nister03]_.
+This function decomposes an essential matrix using :ocv:func:`decomposeEssentialMat` and then verifies possible pose hypotheses by doing cheirality check.
+The cheirality check basically means that the triangulated 3D points should have positive depth. Some details can be found in [Nister03]_.
-This function can be used to process output ``E`` and ``mask`` from ``findEssentialMat()``.
-In this scenario, ``points1`` and ``points2`` are the same input for ``findEssentialMat()``. ::
+This function can be used to process output ``E`` and ``mask`` from :ocv:func:`findEssentialMat`.
+In this scenario, ``points1`` and ``points2`` are the same input for :ocv:func:`findEssentialMat`. ::
// Example. Estimation of fundamental matrix using the RANSAC algorithm
int point_count = 100;