tracking.hpp File Reference

#include "opencv2/core.hpp"
#include "opencv2/imgproc.hpp"

Include dependency graph for tracking.hpp:

This graph shows which files directly or indirectly include this file:

Classes
class	cv::DenseOpticalFlow
class	cv::DISOpticalFlow
	DIS optical flow algorithm. More...
class	cv::FarnebackOpticalFlow
	Class computing a dense optical flow using the Gunnar Farneback's algorithm. More...
class	cv::KalmanFilter
	Kalman filter class. More...
struct	cv::TrackerMIL::Params
struct	cv::TrackerGOTURN::Params
struct	cv::TrackerDaSiamRPN::Params
struct	cv::TrackerNano::Params
struct	cv::TrackerVit::Params
class	cv::SparseOpticalFlow
	Base interface for sparse optical flow algorithms. More...
class	cv::SparsePyrLKOpticalFlow
	Class used for calculating a sparse optical flow. More...
class	cv::Tracker
	Base abstract class for the long-term tracker. More...
class	cv::TrackerDaSiamRPN
class	cv::TrackerGOTURN
	the GOTURN (Generic Object Tracking Using Regression Networks) tracker More...
class	cv::TrackerMIL
	The MIL algorithm trains a classifier in an online manner to separate the object from the background. More...
class	cv::TrackerNano
	the Nano tracker is a super lightweight dnn-based general object tracking. More...
class	cv::TrackerVit
	the VIT tracker is a super lightweight dnn-based general object tracking. More...
class	cv::VariationalRefinement
	Variational optical flow refinement. More...

Namespaces
namespace	cv

Enumerations
enum	{   cv::OPTFLOW_USE_INITIAL_FLOW = 4 ,   cv::OPTFLOW_LK_GET_MIN_EIGENVALS = 8 ,   cv::OPTFLOW_FARNEBACK_GAUSSIAN = 256 }
enum	{   cv::MOTION_TRANSLATION = 0 ,   cv::MOTION_EUCLIDEAN = 1 ,   cv::MOTION_AFFINE = 2 ,   cv::MOTION_HOMOGRAPHY = 3 }

Functions
int	cv::buildOpticalFlowPyramid (InputArray img, OutputArrayOfArrays pyramid, Size winSize, int maxLevel, bool withDerivatives=true, int pyrBorder=BORDER_REFLECT_101, int derivBorder=BORDER_CONSTANT, bool tryReuseInputImage=true)
	Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
void	cv::calcOpticalFlowFarneback (InputArray prev, InputArray next, InputOutputArray flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags)
	Computes a dense optical flow using the Gunnar Farneback's algorithm.
void	cv::calcOpticalFlowPyrLK (InputArray prevImg, InputArray nextImg, InputArray prevPts, InputOutputArray nextPts, OutputArray status, OutputArray err, Size winSize=Size(21, 21), int maxLevel=3, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 30, 0.01), int flags=0, double minEigThreshold=1e-4)
	Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.
RotatedRect	cv::CamShift (InputArray probImage, Rect &window, TermCriteria criteria)
	Finds an object center, size, and orientation.
double	cv::computeECC (InputArray templateImage, InputArray inputImage, InputArray inputMask=noArray())
	Computes the Enhanced Correlation Coefficient value between two images [80] .
Mat	cv::estimateRigidTransform (InputArray src, InputArray dst, bool fullAffine)
	Computes an optimal affine transformation between two 2D point sets.
double	cv::findTransformECC (InputArray templateImage, InputArray inputImage, InputOutputArray warpMatrix, int motionType, TermCriteria criteria, InputArray inputMask, int gaussFiltSize)
	Finds the geometric transform (warp) between two images in terms of the ECC criterion [80] .
double	cv::findTransformECC (InputArray templateImage, InputArray inputImage, InputOutputArray warpMatrix, int motionType=MOTION_AFFINE, TermCriteria criteria=TermCriteria(TermCriteria::COUNT+TermCriteria::EPS, 50, 0.001), InputArray inputMask=noArray())
int	cv::meanShift (InputArray probImage, Rect &window, TermCriteria criteria)
	Finds an object on a back projection image.
Mat	cv::readOpticalFlow (const String &path)
	Read a .flo file.
bool	cv::writeOpticalFlow (const String &path, InputArray flow)
	Write a .flo to disk.