Add a function that draws frame axes. Useful for debugging purpose and to check the correctness of the output of a pose estimation method.

Add Java and Python code for AKAZE local features matching tutorial. Fix incorrect uses of Mat.mul() in Java code.

Uniform Lowe's ratio test in the code.

Add Java and Python code for the following features2d tutorials: Harris corner detector, Shi-Tomasi corner detector, Creating your own corner detector, Detecting corners location in subpixels, Feature Detection, Feature Description, Feature Matching with FLANN, Features2D + Homography to find a known object. Use Lowe's ratio test to filter the matches.

- use per-module includes instead of "opencv.hpp"
- unused function warnings
- undefined macro warning

* Update samples

* Update calib3d.hpp

* Update calib3d.hpp

* Update calib3d.hpp

* Update calib3d.hpp

Update planar_tracking.cpp (#9686)

* Adds cv::resizeWindow() overload taking a single cv::Size argument.

* Replaces copied documentaion with Doxygen @overload command.

Original commit is a5f19f7dd6ae5bc93f73e0417a9e0bfd34c01672

  - previously BB was ignored for first frame, now masks analysis area
  - also allow real-time feedback of processing

(cherry picked from commit 341e7b3b)

(cherry picked from commit bba8c0be)

quickly corrected the previous refactoring of features2d: moved from set(SOME_PROP, val) to setSomeProp(val)

Added the defaultNorm() method to the DescriptorExtractor class. This method returns the default norm type for each descriptor type. The tests and C/C++ samples were updated to get the norm type directly from the DescriptorExtractor inherited classes.

This was reported in feature report #2182 (http://code.opencv.org/issues/2182). It will make it possible to get the norm type usually applied matching method for each descriptor, instead of passing it manually.

Also fixed some typos and code alignment
Also adapted tutorial CPP samples
Fixed some identation problems

If we have perfect matches (min_dist == 0.0), then strict comparison
fails. Making it non-strict results in treating perfect matches as
good.

Made all STL usages explicit to be able automatically find all usages of
particular class or function.