generic-library/opencv
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Fixing documentation links

Browse Source
This commit is contained in:
Philipp Hasper 2014-09-08 14:41:29 +02:00
parent 0b53ca2848
commit cc7aa5890d
1 changed files with 5 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

10
modules/calib3d/doc/camera_calibration_and_3d_reconstruction.rst
View File

@ -740,7 +740,7 @@ where
:math:`E` is an essential matrix, :math:`E` is an essential matrix,
:math:`p_1` and :math:`p_1` and
:math:`p_2` are corresponding points in the first and the second images, respectively. :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 decomposeEssentialMat
------------------------- -------------------------
@ -812,11 +812,11 @@ Returns the number of inliers which pass the check.
Only these inliers will be used to recover pose. Only these inliers will be used to recover pose.
In the output mask only inliers which pass the cheirality check. 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. 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 from [Nister03]_. 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()``. 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 ``findEssentialMat()``. :: In this scenario, ``points1`` and ``points2`` are the same input for :ocv:func:`findEssentialMat`. ::
// Example. Estimation of fundamental matrix using the RANSAC algorithm // Example. Estimation of fundamental matrix using the RANSAC algorithm
int point_count = 100; int point_count = 100;