the weighted orientation histogram, where a recent motion has a larger
weight and the motion occurred in the past has a smaller weight, as recorded in ``mhi`` .
+
+.. index:: segmentMotion
+
+segmentMotion
+-------------
+
+.. cpp:function:: void segmentMotion(InputArray mhi, OutputArray segmask, vector<Rect>& boundingRects, double timestamp, double segThresh)
+
+ Splits a motion history image into a few parts corresponding to separate independent motions (e.g. left hand, right hand).
+
+ :param mhi: Motion history image.
+
+ :param segmask: Image where the mask found should be stored, single-channel, 32-bit floating-point.
+
+ :param boundingRects: Vector that will contain ROIs of motion connected components.
+
+ :param timestamp: Current time in milliseconds or other units.
+
+ :param segThresh: Segmentation threshold; recommended to be equal to the interval between motion history "steps" or greater.
+
+
+ The function finds all of the motion segments and marks them in ``segmask`` with individual values (1,2,...). It also computes a vector with ROIs of motion connected components. After that the motion direction for every component can be calculated with :cpp:func:`calcGlobalOrientation` using the extracted mask of the particular component.
+
+
.. index:: CamShift
CamShift
http://en.wikipedia.org/wiki/Kalman_filter
. However, you can modify ``transitionMatrix``, ``controlMatrix``, and ``measurementMatrix`` to get an extended Kalman filter functionality. See the OpenCV sample ``kalman.cpp`` .
+
+.. index:: KalmanFilter::KalmanFilter
+
KalmanFilter::KalmanFilter
--------------------------
:param type: Type of the created matrices. Should be ``CV_32F`` or ``CV_64F``.
+.. index:: KalmanFilter::init
+
KalmanFilter::init
------------------
:param type: Type of the created matrices. Should be ``CV_32F`` or ``CV_64F``.
+
+.. index:: KalmanFilter::predict
+
KalmanFilter::predict
---------------------
Computes predicted state
+.. index:: KalmanFilter::correct
+
KalmanFilter::correct
---------------------
Updates the predicted state from the measurement
+.. index:: BackgroundSubtractor
+
BackgroundSubtractor
--------------------
The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.
+
+.. index:: BackgroundSubtractor::operator()
+
BackgroundSubtractor::operator()
-------------------------------
:param fgmask: The foreground mask as 8-bit binary image.
+.. index:: BackgroundSubtractor::getBackgroundImage
+
BackgroundSubtractor::getBackgroundImage
----------------------------------------
This method computes a background image.
+.. index:: BackgroundSubtractorMOG
+
BackgroundSubtractorMOG
-----------------------
The class implements the following algorithm: P. KadewTraKuPong and R. Bowden, An improved adaptive background mixture model for real-time tracking with shadow detection, Proc. 2nd European Workshp on Advanced Video-Based Surveillance Systems, 2001: http://personal.ee.surrey.ac.uk/Personal/R.Bowden/publications/avbs01/avbs01.pdf
+.. index:: BackgroundSubtractorMOG::BackgroundSubtractorMOG
+
BackgroundSubtractorMOG::BackgroundSubtractorMOG
------------------------------------------------
Default constructor sets all parameters to some default values.
+.. index:: BackgroundSubtractorMOG::operator()
+
BackgroundSubtractorMOG::operator()
-----------------------------------
The update operator.
+.. index:: BackgroundSubtractorMOG::initialize
+
BackgroundSubtractorMOG::initialize
-----------------------------------
Re-initiaization method.
+.. index:: BackgroundSubtractorMOG2
+
BackgroundSubtractorMOG2
------------------------
* Z.Zivkovic, F. van der Heijden, Efficient Adaptive Density Estimapion per Image Pixel for the Task of Background Subtraction, Pattern Recognition Letters, vol. 27, no. 7, pages 773-780, 2006. The algorithm similar to the standard Stauffer&Grimson algorithm with additional selection of the number of the Gaussian components based on: Z.Zivkovic, F.van der Heijden, Recursive unsupervised learning of finite mixture models, IEEE Trans. on Pattern Analysis and Machine Intelligence, vol.26, no.5, pages 651-656, 2004.
+.. index:: BackgroundSubtractorMOG2::BackgroundSubtractorMOG2
+
BackgroundSubtractorMOG2::BackgroundSubtractorMOG2
--------------------------------------------------
:param fTau: Shadow threshold. The shadow is detected if the pixel is darker version of the background. Tau is a threshold on how much darker the shadow can be. Tau= 0.5 means that if pixel is more than 2 times darker then it is not shadow. See: Prati,Mikic,Trivedi,Cucchiarra,"Detecting Moving Shadows...",IEEE PAMI,2003.
+.. index:: BackgroundSubtractorMOG2::operator()
+
BackgroundSubtractorMOG2::operator()
-----------------------------------
The update operator.
+.. index:: BackgroundSubtractorMOG2::initialize
+
BackgroundSubtractorMOG2::initialize
------------------------------------
Re-initiaization method.
+.. index:: BackgroundSubtractorMOG2::getBackgroundImage
+
BackgroundSubtractorMOG2::getBackgroundImage
--------------------------------------------