From: unknown Date: Fri, 28 Mar 2014 13:23:10 +0000 (+0100) Subject: Python typdef fixed. Reverted the example to MOG2. Not time to make the command line... X-Git-Tag: accepted/tizen/6.0/unified/20201030.111113~3304^2 X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=75534a4828fbb1b7160b6af27c9aa68a1456dda5;p=platform%2Fupstream%2Fopencv.git Python typdef fixed. Reverted the example to MOG2. Not time to make the command line switch for now. --- diff --git a/modules/python/src2/cv2.cpp b/modules/python/src2/cv2.cpp index beb67b4..9ab58e6 100644 --- a/modules/python/src2/cv2.cpp +++ b/modules/python/src2/cv2.cpp @@ -134,6 +134,7 @@ typedef Ptr Ptr_DescriptorMatcher; typedef Ptr Ptr_BackgroundSubtractor; typedef Ptr Ptr_BackgroundSubtractorMOG; typedef Ptr Ptr_BackgroundSubtractorMOG2; +typedef Ptr Ptr_BackgroundSubtractorKNN; typedef Ptr Ptr_BackgroundSubtractorGMG; typedef Ptr 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 --- 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. “Motion Segmentation and Pose Recognition with Motion History Gradientsâ€?, 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. “The Representation and Recognition of Action Using Temporal Templatesâ€?, 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 “An Introduction to the Kalman Filterâ€?, 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 --- 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 bg_model = createBackgroundSubtractorKNN(); + Ptr bg_model = createBackgroundSubtractorMOG2(); Mat img, fgmask, fgimg;