The number of gaussians involved in a mixture is supposed
to be dynamically adjusted. After being increased, the number
of gaussians can't be reduced anymore.

It seems to be a regression as the legacy code
located in modules/legacy/src/bgfg_gaussmix.cpp allows to reduce
such number of gaussians.

changed the way the mean value for each pixel is assigned in the output image.

modified BackgroundSubtractorMOG2::getBackgroundImage so that it can now work with gray-level images.

Fixed an issue with weight assignment causing the resulting GMM weights to be unsorted in BackgroundSubtractorMOG2

Copied errorCovPre to errorCovPost. This allows the correct behaviour of the uncertainty to grow when there is missing data for each predict step.

This should fix that pesky test failure that pops up from time to time.

I don't actually know if the default values should be zeros, but the tests
pass, so...

Looks like we don't actually use them; when creating precompiled headers
with Visual C++, a dummy .cpp is created at build time.

This should allow many algorithms to take advantage of more parallelization
technologies.

initial optical flow was not cleaned during the second call

* added DenseOpticalFlow interface
* moved OpticalFlowDual_TVL1 to src folder

This fixes bug #2075

issue 2526

added recommended number of stripes to parallel_for_, modified some of the functions to use larger stripes (for better performance)

+ Improve performance of calcOpticalFlowSingleScale method
+ Small refactoring

Current results:

IMAGE NAMES          RMSE
Beanbags
Dimetrodon           0.329428
DogDance
Grove2               0.550852
Grove3               1.464699
Hydrangea            0.523277
MiniCooper
RubberWhale          0.367246
Urban2               2.717003
Urban3               4.185070
Venus                0.775422
Walking

Time (for Urban3):
17.490248 sec

+ Fixed warnings
+ Add new function calcOpticalFlow with smaller number of arguments
+ Add asserts to algorithm and remove 'exit(1)'

+ New format for flow data - CV_32C2
+ Memory optimization
+ Cross Bilateral Filter optimization
+ Minor optimizations
+ Sample for calcOpticalFlowSF improved

"SimpleFlow" optical flow estimation algorithm (GSoC project) declaration in includes, implementation, usage example, test

+ Fixed warnings
+ Add new function calcOpticalFlow with smaller number of arguments
+ Add asserts to algorithm and remove 'exit(1)'

+ New format for flow data - CV_32C2
+ Memory optimization
+ Cross Bilateral Filter optimization
+ Minor optimizations
+ Sample for calcOpticalFlowSF improved

declaration in includes, implementation, usage example, test