features2d cleanup: Move several feature detectors and descriptors to opencv_contrib

doc/opencv.bib

@@ -1,12 +1,3 @@
-@incollection{ABD12,
-  author = {Alcantarilla, Pablo Fern{\'a}ndez and Bartoli, Adrien and Davison, Andrew J},
-  title = {KAZE features},
-  booktitle = {Computer Vision--ECCV 2012},
-  year = {2012},
-  pages = {214--227},
-  publisher = {Springer},
-  url = {https://www.doc.ic.ac.uk/~ajd/Publications/alcantarilla_etal_eccv2012.pdf}
-}
 @article{ANB13,
   author = {Pablo Fern{\'{a}}ndez Alcantarilla and Jes{\'{u}}s Nuevo and Adrien Bartoli},
   editor = {Tilo Burghardt and Dima Damen and Walterio W. Mayol{-}Cuevas and Majid Mirmehdi},
@@ -597,14 +588,6 @@ @article{YM11
   doi = {10.5201/ipol.2011.my-asift},
   url = {http://www.ipol.im/pub/algo/my_affine_sift/}
 }
-@inproceedings{LCS11,
-  author = {Leutenegger, Stefan and Chli, Margarita and Siegwart, Roland Yves},
-  title = {BRISK: Binary robust invariant scalable keypoints},
-  booktitle = {Computer Vision (ICCV), 2011 IEEE International Conference on},
-  year = {2011},
-  pages = {2548--2555},
-  publisher = {IEEE}
-}
 @article{Louhichi07,
   author = {Louhichi, H. and Fournel, T. and Lavest, J. M. and Ben Aissia, H.},
   title = {Self-calibration of Scheimpflug cameras: an easy protocol},

doc/py_tutorials/py_feature2d/py_brief/py_brief.markdown

@@ -57,7 +57,7 @@ BRIEF in OpenCV
 
 Below code shows the computation of BRIEF descriptors with the help of CenSurE detector.
 
-note, that you need [opencv contrib](https://github.com/opencv/opencv_contrib)) to use this.
+note, that you need [opencv contrib](https://github.com/opencv/opencv_contrib) to use this.
 @code{.py}
 import numpy as np
 import cv2 as cv

doc/tutorials/features2d/akaze_matching/akaze_matching.markdown

@@ -22,6 +22,8 @@ number of inliers (i.e. matches that fit in the given homography).
 You can find expanded version of this example here:
 <https://github.com/pablofdezalc/test_kaze_akaze_opencv>
 
+\warning You need the [OpenCV contrib module *xfeatures2d*](https://github.com/opencv/opencv_contrib/tree/5.x/modules/xfeatures2d) to be able to use the AKAZE features.
+
 Data
 ----
 
@@ -42,23 +44,23 @@ You can find the images (*graf1.png*, *graf3.png*) and homography (*H1to3p.xml*)
 
 @add_toggle_cpp
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/5.x/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
+    [here](https://github.com/opencv/opencv/5.x/samples/cpp/tutorial_code/features2D/AKAZE_match.cpp)
 
 -   **Code at glance:**
     @include samples/cpp/tutorial_code/features2D/AKAZE_match.cpp
 @end_toggle
 
 @add_toggle_java
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/5.x/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)
+    [here](https://github.com/opencv/opencv/5.x/samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java)
 
 -   **Code at glance:**
     @include samples/java/tutorial_code/features2D/akaze_matching/AKAZEMatchDemo.java
 @end_toggle
 
 @add_toggle_python
 -   **Downloadable code**: Click
-    [here](https://raw.githubusercontent.com/opencv/opencv/5.x/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)
+    [here](https://github.com/opencv/opencv/5.x/samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py)
 
 -   **Code at glance:**
     @include samples/python/tutorial_code/features2D/akaze_matching/AKAZE_match.py

doc/tutorials/features2d/akaze_tracking/akaze_tracking.markdown

@@ -17,6 +17,8 @@ Introduction
 In this tutorial we will compare *AKAZE* and *ORB* local features using them to find matches between
 video frames and track object movements.
 
+\warning You need the [OpenCV contrib module *xfeatures2d*](https://github.com/opencv/opencv_contrib/tree/5.x/modules/xfeatures2d) to be able to use the AKAZE features.
+
 The algorithm is as follows:
 
 -   Detect and describe keypoints on the first frame, manually set object boundaries