GAPI (fluid): Sobel 3x3 optimization: CV_SIMD dynamic dispatching (#13133)

* GAPI (fluid): Sobel 3x3: remove template for run_sobel_row()

* GAPI (fluid): Sobel 3x3: dynamic dispatching of CV_SIMD code

* GAPI (fluid): Sobel 3x3 optimization: fixed CV_SIMD dynamic dispatcher

GAPI (fluid): optimization of Sobel 3x3 (#13070)

* GAPI: performance test for Sobel

* GAPI: performance test for Sobel w/FP32 input

* GAPI: Sobel speedup: 2.5x (U8) up to 10x (float)

* GAPI: Sobel 3x3 to support U8 into S16

* GAPI (fluid): Sobel 3x3 speedup: 10% (uchar), 1.5x (float)

* GAPI (fluid): Sobel 3x3 speedup: +10x (uchar), but -20% (float)

* GAPI (fluid): Sobel 3x3 speedup: +10% (float)

* GAPI (fluid): Sobel 3x3 speedup: +15% (float), +10% (uchar)

* GAPI (fluid): Sobel 3x3: address GCC warnings

* GAPI (fluid): Sobel 3x3: separate *.cpp file w/SIMD code

* GAPI (fluid): Sobel 3x3: fixed AVX2 code, AVX2 speedup 20-50% (uchar), 10-20% (float)

* GAPI (fluid): Sobel 3x3: fix CV_SIMD code for AVX2

* GAPI (fluid): Sobel 3x3: refactor

OpenCV 4.0.0-rc

avoid using of ENABLE_* flags

cap_libv4l depends on an external library (libv4l) yet is still larger
(1966 loc vs 1822 loc).
It was initially introduced copy pasting cap_v4l in order to offload
various color conversions to libv4l.
However nowadays we handle most of the needed color conversions inside
OpenCV. Our own implementation is better tested and (probably) also
better performing. (as it can optionally leverage IPP/ OpenCL)

Currently cap_v4l is better maintained and generally the code is in
better shape. There is however an API
difference in getting unconverted frames:
* on cap_libv4l one need to set `CV_CAP_MODE_GRAY=1` or
`CV_CAP_MODE_YUYV=1`
* on cap_v4l one needs to set `CV_CAP_PROP_CONVERT_RGB=0`

the latter is more flexible though as it also allows accessing undecoded
JPEG images.

fixes #4563

Fix #ifdef CV_SIMD128, should be #if CV_SIMD128.

to verify SIMD code path

docs: fix Kroeger2016 bib reference

move from opencv_contrib

[evolution] Stitching for OpenCV 4.0

* stitching: wrap Stitcher::create for bindings

* provide method for consistent stitcher usage across languages

* samples: add python stitching sample

* port cpp stitching sample to python

* stitching: consolidate Stitcher create methods

* remove Stitcher::createDefault, it returns Stitcher, not Ptr<Stitcher> -> inconsistent API
* deprecate cv::createStitcher and cv::createStitcherScans in favor of Stitcher::create

* stitching: avoid anonymous enum in Stitcher

* ORIG_RESOL should be double
* add documentatiton

* stitching: improve documentation in Stitcher

* stitching: expose estimator in Stitcher

* remove ABI hack

* stitching: drop try_use_gpu flag

* OCL will be used automatically through T-API in OCL-enable paths
* CUDA won't be used unless user sets CUDA-enabled classes manually

* stitching: drop FeaturesFinder

* use Feature2D instead of FeaturesFinder
* interoperability with features2d module
* detach from dependency on xfeatures2d

* features2d: fix compute and detect to work with UMat vectors

* correctly pass UMats as UMats to allow OCL paths
* support vector of UMats as output arg

* stitching: use nearest interpolation for resizing masks

* fix warnings