C# Class Emgu.CV.Features2D.Features2DTracker

This class use ImageFeature to match or track object

Inheritance: DisposableObject

Méthodes publiques

Méthode	Description
CamShiftTrack ( Emgu.CV.Features2D.ImageFeature observedFeatures, MCvBox2D initRegion, Single>.Image priorMask ) : HomographyMatrix	Use camshift to track the feature
Detect ( Emgu.CV.Features2D.ImageFeature observedFeatures, double uniquenessThreshold ) : HomographyMatrix	Detect the if the model features exist in the observed features. If true, an homography matrix is returned, otherwise, null is returned.
Features2DTracker ( Emgu.CV.Features2D.ImageFeature modelFeatures ) : System	Create a Image tracker, where Image is matched with flann
GetHomographyMatrixFromMatchedFeatures ( MatchedImageFeature matchedFeatures ) : HomographyMatrix	Recover the homography matrix using RANDSAC. If the matrix cannot be recovered, null is returned.
MatchFeature ( Emgu.CV.Features2D.ImageFeature observedFeatures, int k, int emax ) : MatchedImageFeature[]	Match the Image feature from the observed image to the features from the model image
VoteForSizeAndOrientation ( MatchedImageFeature matchedFeatures, double scaleIncrement, int rotationBins ) : MatchedImageFeature[]	Eliminate the matched features whose scale and rotation do not aggree with the majority's scale and rotation.
VoteForUniqueness ( MatchedImageFeature matchedFeatures, double uniquenessThreshold ) : MatchedImageFeature[]	Filter the matched Features, such that if a match is not unique, it is rejected.

Méthode	Description
DisposeObject ( ) : void	Release unmanaged memory
ReleaseManagedResources ( ) : void	Release the memory assocaited with this Image Tracker

Use camshift to track the feature

public CamShiftTrack ( Emgu.CV.Features2D.ImageFeature observedFeatures, MCvBox2D initRegion, Single>.Image priorMask ) : HomographyMatrix
observedFeatures	Emgu.CV.Features2D.ImageFeature	The feature found from the observed image
initRegion	MCvBox2D	The predicted location of the model in the observed image. If not known, use MCvBox2D.Empty as default
priorMask	Single>.Image	The mask that should be the same size as the observed image. Contains a priori value of the probability a match can be found. If you are not sure, pass an image fills with 1.0s
Résultat	HomographyMatrix

Detect the if the model features exist in the observed features. If true, an homography matrix is returned, otherwise, null is returned.

public Detect ( Emgu.CV.Features2D.ImageFeature observedFeatures, double uniquenessThreshold ) : HomographyMatrix
observedFeatures	Emgu.CV.Features2D.ImageFeature	The observed features
uniquenessThreshold	double	The distance different ratio which a match is consider unique, a good number will be 0.8
Résultat	HomographyMatrix

Release unmanaged memory

protected DisposeObject ( ) : void
Résultat	void

Create a Image tracker, where Image is matched with flann

public Features2DTracker ( Emgu.CV.Features2D.ImageFeature modelFeatures ) : System
modelFeatures	Emgu.CV.Features2D.ImageFeature	The Image feature from the model image
Résultat	System

Recover the homography matrix using RANDSAC. If the matrix cannot be recovered, null is returned.

public static GetHomographyMatrixFromMatchedFeatures ( MatchedImageFeature matchedFeatures ) : HomographyMatrix
matchedFeatures	MatchedImageFeature	The Matched Features, only the first ModelFeature will be considered
Résultat	HomographyMatrix

Match the Image feature from the observed image to the features from the model image

public MatchFeature ( Emgu.CV.Features2D.ImageFeature observedFeatures, int k, int emax ) : MatchedImageFeature[]
observedFeatures	Emgu.CV.Features2D.ImageFeature	The Image feature from the observed image
k	int	The number of neighbors to find
emax	int	For k-d tree only: the maximum number of leaves to visit.
Résultat	MatchedImageFeature[]

Release the memory assocaited with this Image Tracker

protected ReleaseManagedResources ( ) : void
Résultat	void

Eliminate the matched features whose scale and rotation do not aggree with the majority's scale and rotation.

public static VoteForSizeAndOrientation ( MatchedImageFeature matchedFeatures, double scaleIncrement, int rotationBins ) : MatchedImageFeature[]
matchedFeatures	MatchedImageFeature	The matched feature that will be participated in the voting. For each matchedFeatures, only the zero indexed ModelFeature will be considered.
scaleIncrement	double	This determins the different in scale for neighbour hood bins, a good value might be 1.5 (which means matched features in bin i+1 is scaled 1.5 times larger than matched features in bin i
rotationBins	int	The numbers of bins for rotation, a good value might be 20 (which means each bin covers 18 degree)
Résultat	MatchedImageFeature[]

Filter the matched Features, such that if a match is not unique, it is rejected.

public static VoteForUniqueness ( MatchedImageFeature matchedFeatures, double uniquenessThreshold ) : MatchedImageFeature[]
matchedFeatures	MatchedImageFeature	The Matched Image features, each of them has the model feature sorted by distance. (e.g. SortMatchedFeaturesByDistance )
uniquenessThreshold	double	The distance different ratio which a match is consider unique, a good number will be 0.8
Résultat	MatchedImageFeature[]