public class Video extends Object
Modifier and Type | Field and Description |
---|---|
static int |
MOTION_AFFINE |
static int |
MOTION_EUCLIDEAN |
static int |
MOTION_HOMOGRAPHY |
static int |
MOTION_TRANSLATION |
static int |
OPTFLOW_FARNEBACK_GAUSSIAN |
static int |
OPTFLOW_LK_GET_MIN_EIGENVALS |
static int |
OPTFLOW_USE_INITIAL_FLOW |
Constructor and Description |
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Video() |
Modifier and Type | Method and Description |
---|---|
static int |
buildOpticalFlowPyramid(Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel)
Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
|
static int |
buildOpticalFlowPyramid(Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives)
Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
|
static int |
buildOpticalFlowPyramid(Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives,
int pyrBorder)
Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
|
static int |
buildOpticalFlowPyramid(Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives,
int pyrBorder,
int derivBorder)
Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
|
static int |
buildOpticalFlowPyramid(Mat img,
List<Mat> pyramid,
Size winSize,
int maxLevel,
boolean withDerivatives,
int pyrBorder,
int derivBorder,
boolean tryReuseInputImage)
Constructs the image pyramid which can be passed to calcOpticalFlowPyrLK.
|
static void |
calcOpticalFlowFarneback(Mat prev,
Mat next,
Mat 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.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria,
int flags)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static void |
calcOpticalFlowPyrLK(Mat prevImg,
Mat nextImg,
MatOfPoint2f prevPts,
MatOfPoint2f nextPts,
MatOfByte status,
MatOfFloat err,
Size winSize,
int maxLevel,
TermCriteria criteria,
int flags,
double minEigThreshold)
Calculates an optical flow for a sparse feature set using the iterative Lucas-Kanade method with
pyramids.
|
static RotatedRect |
CamShift(Mat probImage,
Rect window,
TermCriteria criteria)
Finds an object center, size, and orientation.
|
static double |
computeECC(Mat templateImage,
Mat inputImage)
Computes the Enhanced Correlation Coefficient value between two images CITE: EP08 .
|
static double |
computeECC(Mat templateImage,
Mat inputImage,
Mat inputMask)
Computes the Enhanced Correlation Coefficient value between two images CITE: EP08 .
|
static BackgroundSubtractorKNN |
createBackgroundSubtractorKNN()
Creates KNN Background Subtractor
whether a pixel is close to that sample.
|
static BackgroundSubtractorKNN |
createBackgroundSubtractorKNN(int history)
Creates KNN Background Subtractor
|
static BackgroundSubtractorKNN |
createBackgroundSubtractorKNN(int history,
double dist2Threshold)
Creates KNN Background Subtractor
|
static BackgroundSubtractorKNN |
createBackgroundSubtractorKNN(int history,
double dist2Threshold,
boolean detectShadows)
Creates KNN Background Subtractor
|
static BackgroundSubtractorMOG2 |
createBackgroundSubtractorMOG2()
Creates MOG2 Background Subtractor
to decide whether a pixel is well described by the background model.
|
static BackgroundSubtractorMOG2 |
createBackgroundSubtractorMOG2(int history)
Creates MOG2 Background Subtractor
|
static BackgroundSubtractorMOG2 |
createBackgroundSubtractorMOG2(int history,
double varThreshold)
Creates MOG2 Background Subtractor
|
static BackgroundSubtractorMOG2 |
createBackgroundSubtractorMOG2(int history,
double varThreshold,
boolean detectShadows)
Creates MOG2 Background Subtractor
|
static double |
findTransformECC(Mat templateImage,
Mat inputImage,
Mat warpMatrix,
int motionType,
TermCriteria criteria,
Mat inputMask,
int gaussFiltSize)
Finds the geometric transform (warp) between two images in terms of the ECC criterion CITE: EP08 .
|
static int |
meanShift(Mat probImage,
Rect window,
TermCriteria criteria)
Finds an object on a back projection image.
|
static Mat |
readOpticalFlow(String path)
Read a .flo file
|
static boolean |
writeOpticalFlow(String path,
Mat flow)
Write a .flo to disk
|
public static final int OPTFLOW_USE_INITIAL_FLOW
public static final int OPTFLOW_LK_GET_MIN_EIGENVALS
public static final int OPTFLOW_FARNEBACK_GAUSSIAN
public static final int MOTION_TRANSLATION
public static final int MOTION_EUCLIDEAN
public static final int MOTION_AFFINE
public static final int MOTION_HOMOGRAPHY
public static Mat readOpticalFlow(String path)
path
- Path to the file to be loaded
The function readOpticalFlow loads a flow field from a file and returns it as a single matrix.
Resulting Mat has a type CV_32FC2 - floating-point, 2-channel. First channel corresponds to the
flow in the horizontal direction (u), second - vertical (v).public static BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history, double dist2Threshold, boolean detectShadows)
history
- Length of the history.dist2Threshold
- Threshold on the squared distance between the pixel and the sample to decide
whether a pixel is close to that sample. This parameter does not affect the background update.detectShadows
- If true, the algorithm will detect shadows and mark them. It decreases the
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history, double dist2Threshold)
history
- Length of the history.dist2Threshold
- Threshold on the squared distance between the pixel and the sample to decide
whether a pixel is close to that sample. This parameter does not affect the background update.
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorKNN createBackgroundSubtractorKNN(int history)
history
- Length of the history.
whether a pixel is close to that sample. This parameter does not affect the background update.
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorKNN createBackgroundSubtractorKNN()
public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history, double varThreshold, boolean detectShadows)
history
- Length of the history.varThreshold
- Threshold on the squared Mahalanobis distance between the pixel and the model
to decide whether a pixel is well described by the background model. This parameter does not
affect the background update.detectShadows
- If true, the algorithm will detect shadows and mark them. It decreases the
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history, double varThreshold)
history
- Length of the history.varThreshold
- Threshold on the squared Mahalanobis distance between the pixel and the model
to decide whether a pixel is well described by the background model. This parameter does not
affect the background update.
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2(int history)
history
- Length of the history.
to decide whether a pixel is well described by the background model. This parameter does not
affect the background update.
speed a bit, so if you do not need this feature, set the parameter to false.public static BackgroundSubtractorMOG2 createBackgroundSubtractorMOG2()
public static RotatedRect CamShift(Mat probImage, Rect window, TermCriteria criteria)
probImage
- Back projection of the object histogram. See calcBackProject.window
- Initial search window.criteria
- Stop criteria for the underlying meanShift.
returns
(in old interfaces) Number of iterations CAMSHIFT took to converge
The function implements the CAMSHIFT object tracking algorithm CITE: Bradski98 . First, it finds an
object center using meanShift and then adjusts the window size and finds the optimal rotation. The
function returns the rotated rectangle structure that includes the object position, size, and
orientation. The next position of the search window can be obtained with RotatedRect::boundingRect()
See the OpenCV sample camshiftdemo.c that tracks colored objects.
Note:
public static boolean writeOpticalFlow(String path, Mat flow)
path
- Path to the file to be writtenflow
- Flow field to be stored
The function stores a flow field in a file, returns true on success, false otherwise.
The flow field must be a 2-channel, floating-point matrix (CV_32FC2). First channel corresponds
to the flow in the horizontal direction (u), second - vertical (v).public static double computeECC(Mat templateImage, Mat inputImage, Mat inputMask)
templateImage
- single-channel template image; CV_8U or CV_32F array.inputImage
- single-channel input image to be warped to provide an image similar to
templateImage, same type as templateImage.inputMask
- An optional mask to indicate valid values of inputImage.
SEE:
findTransformECCpublic static double computeECC(Mat templateImage, Mat inputImage)
templateImage
- single-channel template image; CV_8U or CV_32F array.inputImage
- single-channel input image to be warped to provide an image similar to
templateImage, same type as templateImage.
SEE:
findTransformECCpublic static double findTransformECC(Mat templateImage, Mat inputImage, Mat warpMatrix, int motionType, TermCriteria criteria, Mat inputMask, int gaussFiltSize)
templateImage
- single-channel template image; CV_8U or CV_32F array.inputImage
- single-channel input image which should be warped with the final warpMatrix in
order to provide an image similar to templateImage, same type as templateImage.warpMatrix
- floating-point \(2\times 3\) or \(3\times 3\) mapping matrix (warp).motionType
- parameter, specifying the type of motion:
warpMatrix\
is \(3\times 3\).criteria
- parameter, specifying the termination criteria of the ECC algorithm;
criteria.epsilon defines the threshold of the increment in the correlation coefficient between two
iterations (a negative criteria.epsilon makes criteria.maxcount the only termination criterion).
Default values are shown in the declaration above.inputMask
- An optional mask to indicate valid values of inputImage.gaussFiltSize
- An optional value indicating size of gaussian blur filter; (DEFAULT: 5)
public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder, boolean tryReuseInputImage)
img
- 8-bit input image.pyramid
- output pyramid.winSize
- window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.maxLevel
- 0-based maximal pyramid level number.withDerivatives
- set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.pyrBorder
- the border mode for pyramid layers.derivBorder
- the border mode for gradients.tryReuseInputImage
- put ROI of input image into the pyramid if possible. You can pass false
to force data copying.public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder, int derivBorder)
img
- 8-bit input image.pyramid
- output pyramid.winSize
- window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.maxLevel
- 0-based maximal pyramid level number.withDerivatives
- set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.pyrBorder
- the border mode for pyramid layers.derivBorder
- the border mode for gradients.
to force data copying.public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives, int pyrBorder)
img
- 8-bit input image.pyramid
- output pyramid.winSize
- window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.maxLevel
- 0-based maximal pyramid level number.withDerivatives
- set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.pyrBorder
- the border mode for pyramid layers.
to force data copying.public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel, boolean withDerivatives)
img
- 8-bit input image.pyramid
- output pyramid.winSize
- window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.maxLevel
- 0-based maximal pyramid level number.withDerivatives
- set to precompute gradients for the every pyramid level. If pyramid is
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.
to force data copying.public static int buildOpticalFlowPyramid(Mat img, List<Mat> pyramid, Size winSize, int maxLevel)
img
- 8-bit input image.pyramid
- output pyramid.winSize
- window size of optical flow algorithm. Must be not less than winSize argument of
calcOpticalFlowPyrLK. It is needed to calculate required padding for pyramid levels.maxLevel
- 0-based maximal pyramid level number.
constructed without the gradients then calcOpticalFlowPyrLK will calculate them internally.
to force data copying.public static int meanShift(Mat probImage, Rect window, TermCriteria criteria)
probImage
- Back projection of the object histogram. See calcBackProject for details.window
- Initial search window.criteria
- Stop criteria for the iterative search algorithm.
returns
: Number of iterations CAMSHIFT took to converge.
The function implements the iterative object search algorithm. It takes the input back projection of
an object and the initial position. The mass center in window of the back projection image is
computed and the search window center shifts to the mass center. The procedure is repeated until the
specified number of iterations criteria.maxCount is done or until the window center shifts by less
than criteria.epsilon. The algorithm is used inside CamShift and, unlike CamShift , the search
window size or orientation do not change during the search. You can simply pass the output of
calcBackProject to this function. But better results can be obtained if you pre-filter the back
projection and remove the noise. For example, you can do this by retrieving connected components
with findContours , throwing away contours with small area ( contourArea ), and rendering the
remaining contours with drawContours.public static void calcOpticalFlowFarneback(Mat prev, Mat next, Mat flow, double pyr_scale, int levels, int winsize, int iterations, int poly_n, double poly_sigma, int flags)
prev
- first 8-bit single-channel input image.next
- second input image of the same size and the same type as prev.flow
- computed flow image that has the same size as prev and type CV_32FC2.pyr_scale
- parameter, specifying the image scale (<1) to build pyramids for each image;
pyr_scale=0.5 means a classical pyramid, where each next layer is twice smaller than the previous
one.levels
- number of pyramid layers including the initial image; levels=1 means that no extra
layers are created and only the original images are used.winsize
- averaging window size; larger values increase the algorithm robustness to image
noise and give more chances for fast motion detection, but yield more blurred motion field.iterations
- number of iterations the algorithm does at each pyramid level.poly_n
- size of the pixel neighborhood used to find polynomial expansion in each pixel;
larger values mean that the image will be approximated with smoother surfaces, yielding more
robust algorithm and more blurred motion field, typically poly_n =5 or 7.poly_sigma
- standard deviation of the Gaussian that is used to smooth derivatives used as a
basis for the polynomial expansion; for poly_n=5, you can set poly_sigma=1.1, for poly_n=7, a
good value would be poly_sigma=1.5.flags
- operation flags that can be a combination of the following:
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria, int flags, double minEigThreshold)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).winSize
- size of the search window at each pyramid level.maxLevel
- 0-based maximal pyramid level number; if set to 0, pyramids are not used (single
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.criteria
- parameter, specifying the termination criteria of the iterative search algorithm
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.flags
- operation flags:
minEigThreshold
- the algorithm calculates the minimum eigen value of a 2x2 normal matrix of
optical flow equations (this matrix is called a spatial gradient matrix in CITE: Bouguet00), divided
by number of pixels in a window; if this value is less than minEigThreshold, then a corresponding
feature is filtered out and its flow is not processed, so it allows to remove bad points and get a
performance boost.
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria, int flags)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).winSize
- size of the search window at each pyramid level.maxLevel
- 0-based maximal pyramid level number; if set to 0, pyramids are not used (single
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.criteria
- parameter, specifying the termination criteria of the iterative search algorithm
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.flags
- operation flags:
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel, TermCriteria criteria)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).winSize
- size of the search window at each pyramid level.maxLevel
- 0-based maximal pyramid level number; if set to 0, pyramids are not used (single
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.criteria
- parameter, specifying the termination criteria of the iterative search algorithm
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize, int maxLevel)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).winSize
- size of the search window at each pyramid level.maxLevel
- 0-based maximal pyramid level number; if set to 0, pyramids are not used (single
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err, Size winSize)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).winSize
- size of the search window at each pyramid level.
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.
public static void calcOpticalFlowPyrLK(Mat prevImg, Mat nextImg, MatOfPoint2f prevPts, MatOfPoint2f nextPts, MatOfByte status, MatOfFloat err)
prevImg
- first 8-bit input image or pyramid constructed by buildOpticalFlowPyramid.nextImg
- second input image or pyramid of the same size and the same type as prevImg.prevPts
- vector of 2D points for which the flow needs to be found; point coordinates must be
single-precision floating-point numbers.nextPts
- output vector of 2D points (with single-precision floating-point coordinates)
containing the calculated new positions of input features in the second image; when
OPTFLOW_USE_INITIAL_FLOW flag is passed, the vector must have the same size as in the input.status
- output status vector (of unsigned chars); each element of the vector is set to 1 if
the flow for the corresponding features has been found, otherwise, it is set to 0.err
- output vector of errors; each element of the vector is set to an error for the
corresponding feature, type of the error measure can be set in flags parameter; if the flow wasn't
found then the error is not defined (use the status parameter to find such cases).
level), if set to 1, two levels are used, and so on; if pyramids are passed to input then
algorithm will use as many levels as pyramids have but no more than maxLevel.
(after the specified maximum number of iterations criteria.maxCount or when the search window
moves by less than criteria.epsilon.
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