Uses of Class
Facemorph.PCA

Packages that use PCA
Facemorph   
Facemorph.aam   
 

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, Mask 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, Mask 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, Mask 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, Mask 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, Mask 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, Mask 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, Mask 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, 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, Mask 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
 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, Mask mask)
          Test method
 

Constructors in Facemorph.aam with parameters of type PCA
CAAMPowell(Mask mask, PCA pca, PCI pci, java.awt.Image subject, Template template)
          Constructor for CAAMPowell