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Added documentation of segmentMotion from cvSegmentMotion doc
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@ -211,6 +211,30 @@ motion direction in the selected region and returns the angle between
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the weighted orientation histogram, where a recent motion has a larger
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weight and the motion occurred in the past has a smaller weight, as recorded in ``mhi`` .
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.. index:: segmentMotion
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segmentMotion
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-------------
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.. cpp:function:: void segmentMotion(InputArray mhi, OutputArray segmask, vector<Rect>& boundingRects, double timestamp, double segThresh)
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Splits a motion history image into a few parts corresponding to separate independent motions (e.g. left hand, right hand).
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:param mhi: Motion history image.
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:param segmask: Image where the mask found should be stored, single-channel, 32-bit floating-point.
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:param boundingRects: Vector that will contain ROIs of motion connected components.
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:param timestamp: Current time in milliseconds or other units.
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:param segThresh: Segmentation threshold; recommended to be equal to the interval between motion history "steps" or greater.
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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.
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.. index:: CamShift
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CamShift
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@ -269,6 +293,9 @@ The class implements a standard Kalman filter
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http://en.wikipedia.org/wiki/Kalman_filter
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. However, you can modify ``transitionMatrix``, ``controlMatrix``, and ``measurementMatrix`` to get an extended Kalman filter functionality. See the OpenCV sample ``kalman.cpp`` .
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.. index:: KalmanFilter::KalmanFilter
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KalmanFilter::KalmanFilter
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--------------------------
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@ -289,6 +316,8 @@ KalmanFilter::KalmanFilter
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:param type: Type of the created matrices. Should be ``CV_32F`` or ``CV_64F``.
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.. index:: KalmanFilter::init
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KalmanFilter::init
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------------------
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@ -304,6 +333,9 @@ KalmanFilter::init
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:param type: Type of the created matrices. Should be ``CV_32F`` or ``CV_64F``.
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.. index:: KalmanFilter::predict
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KalmanFilter::predict
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---------------------
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@ -312,6 +344,8 @@ KalmanFilter::predict
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Computes predicted state
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.. index:: KalmanFilter::correct
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KalmanFilter::correct
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---------------------
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@ -320,6 +354,8 @@ KalmanFilter::correct
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Updates the predicted state from the measurement
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.. index:: BackgroundSubtractor
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BackgroundSubtractor
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--------------------
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@ -338,6 +374,9 @@ The base class for background/foreground segmentation. ::
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The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.
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.. index:: BackgroundSubtractor::operator()
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BackgroundSubtractor::operator()
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-------------------------------
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@ -350,6 +389,8 @@ BackgroundSubtractor::operator()
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:param fgmask: The foreground mask as 8-bit binary image.
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.. index:: BackgroundSubtractor::getBackgroundImage
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BackgroundSubtractor::getBackgroundImage
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----------------------------------------
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@ -358,6 +399,8 @@ BackgroundSubtractor::getBackgroundImage
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This method computes a background image.
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.. index:: BackgroundSubtractorMOG
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BackgroundSubtractorMOG
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-----------------------
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@ -368,6 +411,8 @@ BackgroundSubtractorMOG
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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
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.. index:: BackgroundSubtractorMOG::BackgroundSubtractorMOG
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BackgroundSubtractorMOG::BackgroundSubtractorMOG
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------------------------------------------------
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@ -386,6 +431,8 @@ BackgroundSubtractorMOG::BackgroundSubtractorMOG
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Default constructor sets all parameters to some default values.
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.. index:: BackgroundSubtractorMOG::operator()
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BackgroundSubtractorMOG::operator()
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-----------------------------------
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@ -394,6 +441,8 @@ BackgroundSubtractorMOG::operator()
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The update operator.
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.. index:: BackgroundSubtractorMOG::initialize
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BackgroundSubtractorMOG::initialize
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-----------------------------------
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@ -402,6 +451,8 @@ BackgroundSubtractorMOG::initialize
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Re-initiaization method.
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.. index:: BackgroundSubtractorMOG2
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BackgroundSubtractorMOG2
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------------------------
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@ -416,6 +467,8 @@ The class implements the Gaussian mixture model background subtraction from:
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* 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.
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.. index:: BackgroundSubtractorMOG2::BackgroundSubtractorMOG2
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BackgroundSubtractorMOG2::BackgroundSubtractorMOG2
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--------------------------------------------------
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@ -453,6 +506,8 @@ Also the class has several less important parameters - things you might change b
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: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.
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.. index:: BackgroundSubtractorMOG2::operator()
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BackgroundSubtractorMOG2::operator()
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-----------------------------------
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@ -461,6 +516,8 @@ BackgroundSubtractorMOG2::operator()
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The update operator.
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.. index:: BackgroundSubtractorMOG2::initialize
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BackgroundSubtractorMOG2::initialize
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------------------------------------
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@ -469,6 +526,8 @@ BackgroundSubtractorMOG2::initialize
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Re-initiaization method.
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.. index:: BackgroundSubtractorMOG2::getBackgroundImage
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BackgroundSubtractorMOG2::getBackgroundImage
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--------------------------------------------
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