C# Класс Emgu.CV.OpticalFlow

Contains a collection of optical flow methods

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Открытые методы

Метод	Описание
BM ( Byte>.Image prev, Byte>.Image curr, Size blockSize, Size shiftSize, Size maxRange, bool usePrevious, Single>.Image velx, Single>.Image vely ) : void	Calculates optical flow for overlapped blocks block_size.width * block_size.height pixels each, thus the velocity fields are smaller than the original images. For every block in prev the functions tries to find a similar block in curr in some neighborhood of the original block or shifted by (velx(x0,y0),vely(x0,y0)) block as has been calculated by previous function call (if use_previous)
Farneback ( Byte>.Image prev0, Byte>.Image next0, Single>.Image flowX, Single>.Image flowY, double pyrScale, int levels, int winSize, int iterations, int polyN, double polySigma, CvEnum flags ) : void	Computes dense optical flow using Gunnar Farneback's algorithm
HS ( Byte>.Image prev, Byte>.Image curr, bool usePrevious, Single>.Image velx, Single>.Image vely, double lambda, MCvTermCriteria criteria ) : void	Computes flow for every pixel of the first input image using Horn & Schunck algorithm
LK ( Byte>.Image prev, Byte>.Image curr, Size winSize, Single>.Image velx, Single>.Image vely ) : void	Computes flow for every pixel of the first input image using Lucas & Kanade algorithm
PyrLK ( Byte>.Image prev, Byte>.Image curr, Byte>.Image prevPyrBuffer, Byte>.Image currPyrBuffer, PointF prevFeatures, Size winSize, int level, MCvTermCriteria criteria, Emgu flags, PointF &currFeatures, Byte &status, float &trackError ) : void	Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids
PyrLK ( Byte>.Image prev, Byte>.Image curr, PointF prevFeatures, Size winSize, int level, MCvTermCriteria criteria, PointF &currFeatures, Byte &status, float &trackError ) : void	Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids

Описание методов

BM() публичный статический Метод

Calculates optical flow for overlapped blocks block_size.width * block_size.height pixels each, thus the velocity fields are smaller than the original images. For every block in prev the functions tries to find a similar block in curr in some neighborhood of the original block or shifted by (velx(x0,y0),vely(x0,y0)) block as has been calculated by previous function call (if use_previous)

public static BM ( Byte>.Image prev, Byte>.Image curr, Size blockSize, Size shiftSize, Size maxRange, bool usePrevious, Single>.Image velx, Single>.Image vely ) : void
prev	Byte>.Image	First image
curr	Byte>.Image	Second image
blockSize	System.Drawing.Size	Size of basic blocks that are compared.
shiftSize	System.Drawing.Size	Block coordinate increments.
maxRange	System.Drawing.Size	Size of the scanned neighborhood in pixels around block.
usePrevious	bool	Uses previous (input) velocity field.
velx	Single>.Image	Horizontal component of the optical flow of floor((prev->width - block_size.width)/shiftSize.width) x floor((prev->height - block_size.height)/shiftSize.height) size.
vely	Single>.Image	Vertical component of the optical flow of the same size velx.
Результат	void

Farneback() публичный статический Метод

Computes dense optical flow using Gunnar Farneback's algorithm

public static Farneback ( Byte>.Image prev0, Byte>.Image next0, Single>.Image flowX, Single>.Image flowY, double pyrScale, int levels, int winSize, int iterations, int polyN, double polySigma, CvEnum flags ) : void
prev0	Byte>.Image	The first 8-bit single-channel input image
next0	Byte>.Image	The second input image of the same size and the same type as prevImg
flowX	Single>.Image	The computed flow image for x-velocity; will have the same size as prevImg
flowY	Single>.Image	The computed flow image for y-velocity; will have the same size as prevImg
pyrScale	double	Specifies the image scale (!1) to build the pyramids for each image. pyrScale=0.5 means the classical pyramid, where each next layer is twice smaller than the previous
levels	int	The 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	int	The averaging window size; The larger values increase the algorithm robustness to image noise and give more chances for fast motion detection, but yield more blurred motion field
iterations	int	The number of iterations the algorithm does at each pyramid level
polyN	int	Size of the pixel neighborhood used to find polynomial expansion in each pixel. The 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
polySigma	double	Standard deviation of the Gaussian that is used to smooth derivatives that are 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	CvEnum	The operation flags
Результат	void

HS() публичный статический Метод

Computes flow for every pixel of the first input image using Horn & Schunck algorithm

public static HS ( Byte>.Image prev, Byte>.Image curr, bool usePrevious, Single>.Image velx, Single>.Image vely, double lambda, MCvTermCriteria criteria ) : void
prev	Byte>.Image	First image, 8-bit, single-channel
curr	Byte>.Image	Second image, 8-bit, single-channel
usePrevious	bool	Uses previous (input) velocity field
velx	Single>.Image	Horizontal component of the optical flow of the same size as input images, 32-bit floating-point, single-channel
vely	Single>.Image	Vertical component of the optical flow of the same size as input images, 32-bit floating-point, single-channel
lambda	double	Lagrangian multiplier
criteria	Emgu.CV.Structure.MCvTermCriteria	Criteria of termination of velocity computing
Результат	void

LK() публичный статический Метод

Computes flow for every pixel of the first input image using Lucas & Kanade algorithm

public static LK ( Byte>.Image prev, Byte>.Image curr, Size winSize, Single>.Image velx, Single>.Image vely ) : void
prev	Byte>.Image	First image
curr	Byte>.Image	Second image
winSize	System.Drawing.Size	Size of the averaging window used for grouping pixels
velx	Single>.Image	Horizontal component of the optical flow of the same size as input images
vely	Single>.Image	Vertical component of the optical flow of the same size as input images
Результат	void

PyrLK() публичный статический Метод

Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids

public static PyrLK ( Byte>.Image prev, Byte>.Image curr, Byte>.Image prevPyrBuffer, Byte>.Image currPyrBuffer, PointF prevFeatures, Size winSize, int level, MCvTermCriteria criteria, Emgu flags, PointF &currFeatures, Byte &status, float &trackError ) : void
prev	Byte>.Image	First frame, at time t
curr	Byte>.Image	Second frame, at time t + dt
prevPyrBuffer	Byte>.Image	Buffer for the pyramid for the first frame. If it is not NULL, the buffer must have a sufficient size to store the pyramid from level 1 to level #level ; the total size of (image_width+8)*image_height/3 bytes is sufficient
currPyrBuffer	Byte>.Image	Similar to prev_pyr, used for the second frame
prevFeatures	System.Drawing.PointF	Array of points for which the flow needs to be found
winSize	System.Drawing.Size	Size of the search window of each pyramid level
level	int	Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc
criteria	Emgu.CV.Structure.MCvTermCriteria	Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped
flags	Emgu	Flags
currFeatures	System.Drawing.PointF	Array of 2D points containing calculated new positions of input features in the second image
status	Byte	Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise
trackError	float	Array of double numbers containing difference between patches around the original and moved points
Результат	void

PyrLK() публичный статический Метод

Calculates optical flow for a sparse feature set using iterative Lucas-Kanade method in pyramids

public static PyrLK ( Byte>.Image prev, Byte>.Image curr, PointF prevFeatures, Size winSize, int level, MCvTermCriteria criteria, PointF &currFeatures, Byte &status, float &trackError ) : void
prev	Byte>.Image	First frame, at time t
curr	Byte>.Image	Second frame, at time t + dt
prevFeatures	System.Drawing.PointF	Array of points for which the flow needs to be found
winSize	System.Drawing.Size	Size of the search window of each pyramid level
level	int	Maximal pyramid level number. If 0 , pyramids are not used (single level), if 1 , two levels are used, etc
criteria	Emgu.CV.Structure.MCvTermCriteria	Specifies when the iteration process of finding the flow for each point on each pyramid level should be stopped
currFeatures	System.Drawing.PointF	Array of 2D points containing calculated new positions of input features in the second image
status	Byte	Array. Every element of the array is set to 1 if the flow for the corresponding feature has been found, 0 otherwise
trackError	float	Array of double numbers containing difference between patches around the original and moved points
Результат	void