video library

Classes

BackgroundSubtractorKNN

BackgroundSubtractorMOG2

KalmanFilter

KalmanFilter implements a standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter. However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get an extended Kalman filter functionality.

TrackerMIL

Tracker is the base interface for object tracking.

VideoCapture

VideoWriter

Extensions

BackgroundSubtractorKNNAsync on BackgroundSubtractorKNN

BackgroundSubtractorMOG2Async on BackgroundSubtractorMOG2

KalmanFilterAsync on KalmanFilter

KalmanFilter implements a standard Kalman filter http://en.wikipedia.org/wiki/Kalman_filter. However, you can modify transitionMatrix, controlMatrix, and measurementMatrix to get an extended Kalman filter functionality.

TrackerMILAsync on TrackerMIL

Tracker is the base interface for object tracking.

VideoCaptureAsync on VideoCapture

VideoWriterAsync on VideoWriter

Functions

calcOpticalFlowFarneback(InputArray prev, InputArray next, InputOutputArray flow, double pyrScale, int levels, int winsize, int iterations, int polyN, double polySigma, int flags) → Mat

Apply computes a foreground mask using the current BackgroundSubtractorMOG2.

calcOpticalFlowFarnebackAsync(InputArray prev, InputArray next, InputOutputArray flow, double pyrScale, int levels, int winsize, int iterations, int polyN, double polySigma, int flags) → Future<Mat>

Apply computes a foreground mask using the current BackgroundSubtractorMOG2.

calcOpticalFlowPyrLK(InputArray prevImg, InputArray nextImg, VecPoint2f prevPts, VecPoint2f nextPts, {VecUChar? status, VecF32? err, (int, int) winSize = (21, 21), int maxLevel = 3, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4), int flags = 0, double minEigThreshold = 1e-4}) → (VecPoint2f, VecUChar?, VecF32?)

CalcOpticalFlowPyrLK calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.

calcOpticalFlowPyrLKAsync(InputArray prevImg, InputArray nextImg, VecPoint2f prevPts, VecPoint2f nextPts, {(int, int) winSize = (21, 21), int maxLevel = 3, (int, int, double) criteria = (TERM_COUNT + TERM_EPS, 30, 1e-4), int flags = 0, double minEigThreshold = 1e-4}) → Future<(VecPoint2f, VecUChar, VecF32)>

CalcOpticalFlowPyrLK calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with pyramids.

createBackgroundSubtractorMOG2({int history = 500, double varThreshold = 16, bool detectShadows = true}) → BackgroundSubtractorMOG2

NewBackgroundSubtractorMOG2 returns a new BackgroundSubtractor algorithm of type MOG2. MOG2 is a Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

createBackgroundSubtractorMOG2Async({int history = 500, double varThreshold = 16, bool detectShadows = true}) → Future<BackgroundSubtractorMOG2>

NewBackgroundSubtractorMOG2 returns a new BackgroundSubtractor algorithm of type MOG2. MOG2 is a Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

findTransformECC(InputArray templateImage, InputArray inputImage, InputOutputArray warpMatrix, int motionType, (int, int, double) criteria, InputArray inputMask, int gaussFiltSize) → (double, Mat)

FindTransformECC finds the geometric transform (warp) between two images in terms of the ECC criterion.

findTransformECCAsync(InputArray templateImage, InputArray inputImage, InputOutputArray warpMatrix, int motionType, (int, int, double) criteria, InputArray inputMask, int gaussFiltSize) → Future<(double, Mat)>

FindTransformECC finds the geometric transform (warp) between two images in terms of the ECC criterion.