mirror of
https://github.com/opencv/opencv.git
synced 2024-12-11 14:39:11 +08:00
96 lines
2.3 KiB
Markdown
96 lines
2.3 KiB
Markdown
|
2D Features framework (feature2d module) {#tutorial_table_of_content_features2d}
|
||
|
|
=========================================
|
||
|
|
|
||
|
|
Learn about how to use the feature points detectors, descriptors and matching framework found inside
|
||
|
|
OpenCV.
|
||
|
|
|
||
|
|
- @subpage tutorial_harris_detector
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
Why is it a good idea to track corners? We learn to use the Harris method to detect
|
||
|
|
corners
|
||
|
|
|
||
|
|
- @subpage tutorial_good_features_to_track
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
Where we use an improved method to detect corners more accuratelyI
|
||
|
|
|
||
|
|
- @subpage tutorial_generic_corner_detector
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
Here you will learn how to use OpenCV functions to make your personalized corner detector!
|
||
|
|
|
||
|
|
- @subpage tutorial_corner_subpixeles
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
Is pixel resolution enough? Here we learn a simple method to improve our accuracy.
|
||
|
|
|
||
|
|
- @subpage tutorial_feature_detection
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
In this tutorial, you will use *features2d* to detect interest points.
|
||
|
|
|
||
|
|
- @subpage tutorial_feature_description
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
In this tutorial, you will use *features2d* to calculate feature vectors.
|
||
|
|
|
||
|
|
- @subpage tutorial_feature_flann_matcher
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
In this tutorial, you will use the FLANN library to make a fast matching.
|
||
|
|
|
||
|
|
- @subpage tutorial_feature_homography
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Ana Huamán
|
||
|
|
|
||
|
|
In this tutorial, you will use *features2d* and *calib3d* to detect an object in a scene.
|
||
|
|
|
||
|
|
- @subpage tutorial_detection_of_planar_objects
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 2.0
|
||
|
|
|
||
|
|
*Author:* Victor Eruhimov
|
||
|
|
|
||
|
|
You will use *features2d* and *calib3d* modules for detecting known planar objects in
|
||
|
|
scenes.
|
||
|
|
|
||
|
|
- @subpage tutorial_akaze_matching
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 3.0
|
||
|
|
|
||
|
|
*Author:* Fedor Morozov
|
||
|
|
|
||
|
|
Using *AKAZE* local features to find correspondence between two images.
|
||
|
|
|
||
|
|
- @subpage tutorial_akaze_tracking
|
||
|
|
|
||
|
|
*Compatibility:* \> OpenCV 3.0
|
||
|
|
|
||
|
|
*Author:* Fedor Morozov
|
||
|
|
|
||
|
|
Using *AKAZE* and *ORB* for planar object tracking.
|