video: clean up bg subtraction tutorial

doc/tutorials/video/background_subtraction/background_subtraction.markdown

@@ -40,9 +40,7 @@ Code
 In the following you can find the source code. We will let the user chose to process either a video
 file or a sequence of images.
 
-Two different methods are used to generate two foreground masks:
--#  cv::bgsegm::BackgroundSubtractorMOG
--#  @ref cv::BackgroundSubtractorMOG2
+We will use @ref cv::BackgroundSubtractorMOG2 in this sample, to generate the foreground mask.
 
 The results as well as the input data are shown on the screen.
 The source file can be downloaded [here ](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/video/bg_sub.cpp).
@@ -54,22 +52,19 @@ Explanation
 
 We discuss the main parts of the above code:
 
--#  First, three Mat objects are allocated to store the current frame and two foreground masks,
+-#  First, two Mat objects are allocated to store the current frame and two foreground masks,
     obtained by using two different BS algorithms.
     @code{.cpp}
     Mat frame; //current frame
-    Mat fgMaskMOG; //fg mask generated by MOG method
     Mat fgMaskMOG2; //fg mask fg mask generated by MOG2 method
     @endcode
--#  Two @ref cv::BackgroundSubtractor objects will be used to generate the foreground masks. In this
+-#  A @ref cv::BackgroundSubtractor object will be used to generate the foreground mask. In this
     example, default parameters are used, but it is also possible to declare specific parameters in
     the create function.
     @code{.cpp}
-    Ptr<BackgroundSubtractor> pMOG; //MOG Background subtractor
     Ptr<BackgroundSubtractor> pMOG2; //MOG2 Background subtractor
     ...
-    //create Background Subtractor objects
-    pMOG = createBackgroundSubtractorMOG(); //MOG approach
+    //create Background Subtractor object
     pMOG2 = createBackgroundSubtractorMOG2(); //MOG2 approach
     @endcode
 -#  The command line arguments are analysed. The user can chose between two options:
@@ -101,7 +96,6 @@ We discuss the main parts of the above code:
     set a specific learning rate by passing a third parameter to the 'apply' method.
     @code{.cpp}
     //update the background model
-    pMOG->apply(frame, fgMaskMOG);
     pMOG2->apply(frame, fgMaskMOG2);
     @endcode
 -#  The current frame number can be extracted from the @ref cv::VideoCapture object and stamped in
@@ -121,7 +115,6 @@ We discuss the main parts of the above code:
     @code{.cpp}
     //show the current frame and the fg masks
     imshow("Frame", frame);
-    imshow("FG Mask MOG", fgMaskMOG);
     imshow("FG Mask MOG 2", fgMaskMOG2);
     @endcode
 -#  The same operations listed above can be performed using a sequence of images as input. The