| OpenCV 5.0.0alpha Open Source Computer Vision

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tracking.hpp File Reference
`#include "opencv2/core.hpp"`
`#include "opencv2/imgproc.hpp"`
Include dependency graph for tracking.hpp:
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## 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::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::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.