CvInvokeCalcOpticalFlowFarneback Method (IInputArray, IInputArray, IInputOutputArray, Double, Int32, Int32, Int32, Int32, Double, OpticalflowFarnebackFlag)

public static void CalcOpticalFlowFarneback(
	IInputArray prev0,
	IInputArray next0,
	IInputOutputArray flow,
	double pyrScale,
	int levels,
	int winSize,
	int iterations,
	int polyN,
	double polySigma,
	OpticalflowFarnebackFlag flags
)

Public Shared Sub CalcOpticalFlowFarneback ( 
	prev0 As IInputArray,
	next0 As IInputArray,
	flow As IInputOutputArray,
	pyrScale As Double,
	levels As Integer,
	winSize As Integer,
	iterations As Integer,
	polyN As Integer,
	polySigma As Double,
	flags As OpticalflowFarnebackFlag
)

public:
static void CalcOpticalFlowFarneback(
	IInputArray^ prev0, 
	IInputArray^ next0, 
	IInputOutputArray^ flow, 
	double pyrScale, 
	int levels, 
	int winSize, 
	int iterations, 
	int polyN, 
	double polySigma, 
	OpticalflowFarnebackFlag flags
)

static member CalcOpticalFlowFarneback : 
        prev0 : IInputArray * 
        next0 : IInputArray * 
        flow : IInputOutputArray * 
        pyrScale : float * 
        levels : int * 
        winSize : int * 
        iterations : int * 
        polyN : int * 
        polySigma : float * 
        flags : OpticalflowFarnebackFlag -> unit 

Parameters

prev0

Type: Emgu.CVIInputArray
The first 8-bit single-channel input image

next0

Type: Emgu.CVIInputArray
The second input image of the same size and the same type as prevImg

flow

Type: Emgu.CVIInputOutputArray
The computed flow image; will have the same size as prevImg and type CV 32FC2

pyrScale

Type: SystemDouble
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

Type: SystemInt32
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

Type: SystemInt32
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

Type: SystemInt32
The number of iterations the algorithm does at each pyramid level

polyN

Type: SystemInt32
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

Type: SystemDouble
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

Type: Emgu.CV.CvEnumOpticalflowFarnebackFlag
The operation flags

Reference