potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-30 07:43:03 +04:00
Code Packages Releases Wiki Activity

doc: tutorial refactor

Browse Source
This commit is contained in:
Maksim Shabunin
2020-12-05 01:46:00 +03:00
parent 6fdb7aee84
commit 461e26b60b
263 changed files with 623 additions and 878 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/tutorials/calib3d/camera_calibration/camera_calibration.markdown
+5
View File
@@ -4,6 +4,11 @@ Camera calibration With OpenCV {#tutorial_camera_calibration}
@prev_tutorial{tutorial_camera_calibration_square_chess}
@next_tutorial{tutorial_real_time_pose}
| | |
| -: | :- |
| Original author | Bernát Gábor |
| Compatibility | OpenCV >= 4.0 |
Cameras have been around for a long-long time. However, with the introduction of the cheap *pinhole*
cameras in the late 20th century, they became a common occurrence in our everyday life.
doc/tutorials/calib3d/camera_calibration_pattern/camera_calibration_pattern.markdown
+5
View File
@@ -3,6 +3,11 @@ Create calibration pattern {#tutorial_camera_calibration_pattern}
@next_tutorial{tutorial_camera_calibration_square_chess}
| | |
| -: | :- |
| Original author | Laurent Berger |
| Compatibility | OpenCV >= 3.0 |
The goal of this tutorial is to learn how to create calibration pattern.
doc/tutorials/calib3d/camera_calibration_square_chess/camera_calibration_square_chess.markdown
+5
View File
@@ -4,6 +4,11 @@ Camera calibration with square chessboard {#tutorial_camera_calibration_square_c
@prev_tutorial{tutorial_camera_calibration_pattern}
@next_tutorial{tutorial_camera_calibration}
| | |
| -: | :- |
| Original author | Victor Eruhimov |
| Compatibility | OpenCV >= 4.0 |
The goal of this tutorial is to learn how to calibrate a camera given a set of chessboard images.
doc/tutorials/calib3d/images/camera_calibration.png
BIN
View File
Binary file not shown.
Side by Side

Before

Width:  |  Height:  |  Size: 8.0 KiB

doc/tutorials/calib3d/images/camera_calibration_square_chess.jpg
BIN
View File
Binary file not shown.
Side by Side

Before

Width:  |  Height:  |  Size: 6.6 KiB

doc/tutorials/calib3d/images/real_time_pose_estimation.jpg
BIN
View File
Binary file not shown.
Side by Side

Before

Width:  |  Height:  |  Size: 83 KiB

doc/tutorials/calib3d/interactive_calibration/interactive_calibration.markdown
+5
View File
@@ -3,6 +3,11 @@ Interactive camera calibration application {#tutorial_interactive_calibration}
@prev_tutorial{tutorial_real_time_pose}
| | |
| -: | :- |
| Original author | Vladislav Sovrasov |
| Compatibility | OpenCV >= 3.1 |
According to classical calibration technique user must collect all data first and when run @ref cv::calibrateCamera function
to obtain camera parameters. If average re-projection error is huge or if estimated parameters seems to be wrong, process of
doc/tutorials/calib3d/real_time_pose/real_time_pose.markdown
+5
View File
@@ -4,6 +4,11 @@ Real Time pose estimation of a textured object {#tutorial_real_time_pose}
@prev_tutorial{tutorial_camera_calibration}
@next_tutorial{tutorial_interactive_calibration}
| | |
| -: | :- |
| Original author | Edgar Riba |
| Compatibility | OpenCV >= 3.0 |
Nowadays, augmented reality is one of the top research topic in computer vision and robotics fields.
The most elemental problem in augmented reality is the estimation of the camera pose respect of an
doc/tutorials/calib3d/table_of_content_calib3d.markdown
-50
View File
@@ -1,58 +1,8 @@
Camera calibration and 3D reconstruction (calib3d module) {#tutorial_table_of_content_calib3d}
==========================================================
Although we get most of our images in a 2D format they do come from a 3D world. Here you will learn how to find out 3D world information from 2D images.
- @subpage tutorial_camera_calibration_pattern
*Languages:* Python
*Compatibility:* \> OpenCV 2.0
*Author:* Laurent Berger
You will learn how to create some calibration pattern.
- @subpage tutorial_camera_calibration_square_chess
*Languages:* C++
*Compatibility:* \> OpenCV 2.0
*Author:* Victor Eruhimov
You will use some chessboard images to calibrate your camera.
- @subpage tutorial_camera_calibration
*Languages:* C++
*Compatibility:* \> OpenCV 4.0
*Author:* Bernát Gábor
Camera calibration by using either the chessboard, circle or the asymmetrical circle
pattern. Get the images either from a camera attached, a video file or from an image
collection.
- @subpage tutorial_real_time_pose
*Languages:* C++
*Compatibility:* \> OpenCV 2.0
*Author:* Edgar Riba
Real time pose estimation of a textured object using ORB features, FlannBased matcher, PnP
approach plus Ransac and Linear Kalman Filter to reject possible bad poses.
- @subpage tutorial_interactive_calibration
*Compatibility:* \> OpenCV 3.1
*Author:* Vladislav Sovrasov
Camera calibration by using either the chessboard, chAruco, asymmetrical circle or dual asymmetrical circle
pattern. Calibration process is continuous, so you can see results after each new pattern shot.
As an output you get average reprojection error, intrinsic camera parameters, distortion coefficients and
confidence intervals for all of evaluated variables.