Package org.bytedeco.opencv.opencv_video

Class Summary

Class	Description
BackgroundSubtractor	\addtogroup video_motion \{ /** \brief Base class for background/foreground segmentation. : The class is only used to define the common interface for the whole family of background/foreground segmentation algorithms.
BackgroundSubtractorKNN	\brief K-nearest neighbours - based Background/Foreground Segmentation Algorithm.
BackgroundSubtractorMOG2	\brief Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
DenseOpticalFlow	Base class for dense optical flow algorithms
DISOpticalFlow	\brief DIS optical flow algorithm.
ECCParameters	\brief struct ECCParameters is used by findTransformECCMultiScale
FarnebackOpticalFlow	\brief Class computing a dense optical flow using the Gunnar Farneback's algorithm.
KalmanFilter	\brief Kalman filter class.
SparseOpticalFlow	\brief Base interface for sparse optical flow algorithms.
SparsePyrLKOpticalFlow	\brief Class used for calculating a sparse optical flow.
Tracker	\brief Base abstract class for the long-term tracker
TrackerDaSiamRPN
TrackerDaSiamRPN.Params
TrackerGOTURN	\brief the GOTURN (Generic Object Tracking Using Regression Networks) tracker GOTURN (\cite GOTURN) is kind of trackers based on Convolutional Neural Networks (CNN).
TrackerGOTURN.Params
TrackerMIL	\brief The MIL algorithm trains a classifier in an online manner to separate the object from the background.
TrackerMIL.Params
TrackerNano	\brief the Nano tracker is a super lightweight dnn-based general object tracking.
TrackerNano.Params
TrackerVit	\brief the VIT tracker is a super lightweight dnn-based general object tracking.
TrackerVit.Params
VariationalRefinement	\brief Variational optical flow refinement This class implements variational refinement of the input flow field, i.e. it uses input flow to initialize the minimization of the following functional: E(U) = \int_{\Omega} \delta \Psi(E_I) + \gamma \Psi(E_G) + \alpha \Psi(E_S) , where E_I,E_G,E_S are color constancy, gradient constancy and smoothness terms respectively.