Uses of Class
Facemorph.PCA

Packages that use PCA

Facemorph
Facemorph.aam
Facemorph.Stats

Uses of PCA in Facemorph

Methods in Facemorph that return PCA

PCA	ASM.getPCA() Return the PCA data currently being used
PCA	PCA.getReduced(int max) Gets a copy of this PCA with fewer components

Methods in Facemorph with parameters of type PCA

static void	PCA.addToAverage(Template average1, PCA pca1, Template currentAverage, int n, int start, BigMat data) Incrementally updates the data matrix and currentAverage by adding the PCA data to them
static Template	Template.autoDelineate(java.awt.Image subjectImage, java.awt.Image averageImage, Template averageTemplate, java.awt.geom.Point2D.Float leftEye, java.awt.geom.Point2D.Float rightEye, java.awt.geom.Point2D.Float mouth, int leftIndex, int rightIndex, int mouthIndex, java.awt.image.ImageObserver ob, PCA pca) Automatically delineates the image given returning a Template outlining the facial features
Template	PCA.combine(PCA pca1, Template average1, PCA pca2, Template average2) Combine two PCA models into a single one.
Template	PCA.combine2(PCA pca1, Template average1, PCA pca2, Template average2) Combine two PCA models into a single one.
void	Template.fitAAM(int warpType, java.awt.Image subject, java.awt.Image average, MaskInterface mask, PCA pca, PCI pci) Fits a Template to this FloatImage using a multiscale method
void	Template.fitAAMappearance(int warpType, java.awt.Image subject, java.awt.Image averageImg, MaskInterface mask, PCA pca, PCI pci, float scale) Attempt at fitting an AAM to an image using efficient reverse method, includes colour information
void	Template.fitAAMbayesian(int warpType, java.awt.Image subject, java.awt.Image averageImg, MaskInterface mask, PCA pca, PCI pci, float scale) Attempt at fitting an AAM to an image using efficient reverse method, includes colour information
void	Template.fitAAMforward(java.awt.Image subjectImg, java.awt.Image averageImg, MaskInterface mask, PCA pca, PCI pci, float scale) Attempt at fitting an AAM to an image using inefficient, but more reliable forward method, includes colour information
void	Template.fitAAMshape(int warpType, FloatImage average, FloatImage subject, Template avrg, MaskInterface mask, PCA pca, float scale) First attempt at fitting an AAM to an image, does not include colour information, not recommended to use!
int	Template.fitAAMspan(int warpType, java.awt.Image subject, java.awt.Image averageImg, MaskInterface mask, PCA pca, PCI pci, FloatImage[] smallPCIcomps, float scale, int counter) Attempt at fitting an AAM to an image using efficient reverse method, colour information is projected out
int	Template.fitAAMspanLM(int warpType, java.awt.Image subject, java.awt.Image averageImg, MaskInterface mask, PCA pca, PCI pci, float scale, int counter) Attempt at fitting an AAM to an image using efficient reverse method, includes colour information
void	Template.fitPCA(FloatImage average, FloatImage subject, Template avrg, PCA pca) Fits a Template to this FloatImage
void	Template.fitPCA(FloatImage average, FloatImage subject, Template avrg, PCA pca, int leftIndex, int rightIndex, int mouthIndex) Fits a Template to this FloatImage
boolean	Template.fitPCA(java.awt.Image subjectImage, java.awt.Image averageImage, Template averageTemplate, java.awt.geom.Point2D.Float leftEye, java.awt.geom.Point2D.Float rightEye, int leftIndex, int rightIndex, java.awt.image.ImageObserver ob, PCA pca) Automatically delineates the image given using this Template to outline the facial features
boolean	Template.fitPCA(java.awt.Image subjectImage, java.awt.Image averageImage, Template averageTemplate, java.awt.geom.Point2D.Float leftEye, java.awt.geom.Point2D.Float rightEye, java.awt.geom.Point2D.Float mouth, int leftIndex, int rightIndex, int mouthIndex, java.awt.image.ImageObserver ob, PCA pca) Automatically delineates the image given using this Template to outline the facial features
boolean	Template.fitPCAColourSegment(java.awt.Image subjectImage, java.awt.Image averageImage, Template averageTemplate, java.awt.geom.Point2D.Float leftEye, java.awt.geom.Point2D.Float rightEye, java.awt.geom.Point2D.Float mouth, int leftIndex, int rightIndex, int mouthIndex, java.awt.image.ImageObserver ob, PCA pca, MaskInterface mask) Automatically delineates the image given using this Template to outline the facial features Tries to segment out the face from the background using colour to help
boolean	Template.fitPCARigid(java.awt.Image subjectImage, java.awt.Image averageImage, Template averageTemplate, java.awt.geom.Point2D.Float leftEye, java.awt.geom.Point2D.Float rightEye, java.awt.geom.Point2D.Float mouth, int leftIndex, int rightIndex, int mouthIndex, java.awt.image.ImageObserver ob, PCA pca) Automatically delineates the image given using this Template to outline the facial features
Template[]	PCA.getIntersection(Template average1, Template average2, PCA pca, double alpha, double beta) Find the least squares intersection between the two PCA models
float[]	Template.getPCAandNormParameters(PCA pca, Template average, int normalisation, int[] normPoints) Gets the pca and normalisation parameters in a single vector
float[]	Template.getPCAandRBparameters(PCA pca, Template average) Analyses this Template using a set of principal components
float[]	Template.getPCAparameters(PCA pca, Template average, int leftIndex, int rightIndex, int mouthIndex) Analyses this Template using a set of principal components
boolean	Template.readPCA(java.io.DataInputStream in, Template average, PCA pca, int le, int re, int m) Reads in 3 normalisation points and some PCA parameters and reconstructs the Template (I think!)
void	Template.reconstructPCA(PCA pca, Template average, float[] pcaParams, int toskip) Reconstruct this Template from PCA data
void	Template.reconstructPCA(PCA pca, Template average, java.awt.geom.Point2D.Float left, java.awt.geom.Point2D.Float right, java.awt.geom.Point2D.Float mouth, float[] pcaParams, int leftIndex, int rightIndex, int mouthIndex) Builds a Template from a set of PCA parameters and data
void	Template.reconstructPCAandNorm(PCA pca, Template average, float[] PCAandRBparams, int normalisation, int[] normPoints) Reconstructs this Template from the PCA data using the parameters and normalisation specified
void	Template.reconstructPCAandRB(PCA pca, Template average, float[] PCAandRBparams) Builds a Template from a set of PCA and Rigid Body parameters and data
void	Template.trackASM(FloatImage average, FloatImage subject, Template avrg, PCA pca, float scale, int its, int[] normalisePointIndex) Fits a PCA model to an image using edge normal profiles

Constructors in Facemorph with parameters of type PCA

ASM(Template template, PCA pca, java.awt.Image image, int normalisation, int[] pindex)
Creates a new instance of an ASM using the data specified

Uses of PCA in Facemorph.aam

Methods in Facemorph.aam with parameters of type PCA

static void

CAAMPowell.test(java.lang.String listFile, java.lang.String resFile, PCI pci, PCA pca, MaskInterface mask) Test method

Constructors in Facemorph.aam with parameters of type PCA

CAAMPowell(MaskInterface mask, PCA pca, PCI pci, java.awt.Image subject, Template template)
Constructor for CAAMPowell

Uses of PCA in Facemorph.Stats

Fields in Facemorph.Stats declared as PCA

protected PCA

PCAReducer.pca