Python typdef fixed. Reverted the example to MOG2. Not time to make the command line...

diff --git a/modules/python/src2/cv2.cpp b/modules/python/src2/cv2.cpp
index beb67b4..9ab58e6 100644 (file)
--- a/modules/python/src2/cv2.cpp
+++ b/modules/python/src2/cv2.cpp
@@ -134,6 +134,7 @@ typedef Ptr<DescriptorMatcher> Ptr_DescriptorMatcher;
 typedef Ptr<BackgroundSubtractor> Ptr_BackgroundSubtractor;
 typedef Ptr<BackgroundSubtractorMOG> Ptr_BackgroundSubtractorMOG;
 typedef Ptr<BackgroundSubtractorMOG2> Ptr_BackgroundSubtractorMOG2;
+typedef Ptr<BackgroundSubtractorKNN> Ptr_BackgroundSubtractorKNN;
 typedef Ptr<BackgroundSubtractorGMG> Ptr_BackgroundSubtractorGMG;
 
 typedef Ptr<StereoMatcher> Ptr_StereoMatcher;

diff --git a/modules/video/doc/motion_analysis_and_object_tracking.rst b/modules/video/doc/motion_analysis_and_object_tracking.rst
index e8ec3b3..7d5d1d5 100644 (file)
--- a/modules/video/doc/motion_analysis_and_object_tracking.rst
+++ b/modules/video/doc/motion_analysis_and_object_tracking.rst
@@ -780,7 +780,7 @@ Sets the threshold on the squared distance
 
 BackgroundSubtractorKNN::getkNNSamples
 ---------------------------------------------
-Returns the k in the kNN. K is the number of samples that need to be within dist2Threshold in order to decide that that pixel is matching the kNN background model.
+Returns the number of neighbours, the k in the kNN. K is the number of samples that need to be within dist2Threshold in order to decide that that pixel is matching the kNN background model.
 
 .. ocv:function:: int BackgroundSubtractorKNN::getkNNSamples() const
 
@@ -1108,9 +1108,9 @@ Releases all inner buffers.
 
 .. [Bradski98] Bradski, G.R. "Computer Vision Face Tracking for Use in a Perceptual User Interface", Intel, 1998
 
-.. [Bradski00] Davis, J.W. and Bradski, G.R. â\80\9cMotion Segmentation and Pose Recognition with Motion History Gradientsâ\80?, WACV00, 2000
+.. [Bradski00] Davis, J.W. and Bradski, G.R. "Motion Segmentation and Pose Recognition with Motion History Gradients", WACV00, 2000
 
-.. [Davis97] Davis, J.W. and Bobick, A.F. â\80\9cThe Representation and Recognition of Action Using Temporal Templatesâ\80?, CVPR97, 1997
+.. [Davis97] Davis, J.W. and Bobick, A.F. "The Representation and Recognition of Action Using Temporal Templates", CVPR97, 1997
 
 .. [EP08] Evangelidis, G.D. and Psarakis E.Z. "Parametric Image Alignment using Enhanced Correlation Coefficient Maximization", IEEE Transactions on PAMI, vol. 32, no. 10, 2008
 
@@ -1124,7 +1124,7 @@ Releases all inner buffers.
 
 .. [Lucas81] Lucas, B., and Kanade, T. An Iterative Image Registration Technique with an Application to Stereo Vision, Proc. of 7th International Joint Conference on Artificial Intelligence (IJCAI), pp. 674-679.
 
-.. [Welch95] Greg Welch and Gary Bishop â\80\9cAn Introduction to the Kalman Filterâ\80?, 1995
+.. [Welch95] Greg Welch and Gary Bishop "An Introduction to the Kalman Filter", 1995
 
 .. [Tao2012] Michael Tao, Jiamin Bai, Pushmeet Kohli and Sylvain Paris. SimpleFlow: A Non-iterative, Sublinear Optical Flow Algorithm. Computer Graphics Forum (Eurographics 2012)
 

diff --git a/samples/cpp/bgfg_segm.cpp b/samples/cpp/bgfg_segm.cpp
index de57ef3..a3d0200 100644 (file)
--- a/samples/cpp/bgfg_segm.cpp
+++ b/samples/cpp/bgfg_segm.cpp
@@ -52,7 +52,7 @@ int main(int argc, const char** argv)
     namedWindow("foreground image", WINDOW_NORMAL);
     namedWindow("mean background image", WINDOW_NORMAL);
 
-    Ptr<BackgroundSubtractor> bg_model = createBackgroundSubtractorKNN();
+    Ptr<BackgroundSubtractor> bg_model = createBackgroundSubtractorMOG2();
 
     Mat img, fgmask, fgimg;