Comment PCA est-elle implémentée sur une image capturée de caméra?

Question

J'ai réussi à mettre en œuvre une partie de détection de visage dans mon projet de reconnaissance faciale. Maintenant, j'ai une région rectangulaire de visage dans une image. Maintenant, je dois implémenter PCA sur cette région rectangulaire détectée pour extraire des caractéristiques importantes.J'ai utilisé des exemples de mise en œuvre de l'ACP sur le visage Bases de données.Je veux savoir comment nous pouvons passer notre visage détecté à la fonction implémentant PCA? Est-ce que nous passons le cadre rectangle? Ceci est le code de ma détection de visage.

#include "cv.h"
#include "highgui.h"

#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <assert.h>
#include <math.h>
#include <float.h>
#include <limits.h>
#include <time.h>
#include <ctype.h>


// Create a string that contains the exact cascade name
const char* cascade_name =
    "haarcascade_frontalface_alt.xml";
/*    "haarcascade_profileface.xml";*/


// Function prototype for detecting and drawing an object from an image
void detect_and_draw( IplImage* image );

// Main function, defines the entry point for the program.
int main( int argc, char** argv )
{

    // Create a sample image
    IplImage *img = cvLoadImage("Image018.jpg");
    if(!img)
    {
        printf("could not load image");
        return -1;
    }

    // Call the function to detect and draw the face positions
    detect_and_draw(img);

    // Wait for user input before quitting the program
    cvWaitKey();

    // Release the image
    cvReleaseImage(&img);

    // Destroy the window previously created with filename: "result"
    cvDestroyWindow("result");

    // return 0 to indicate successfull execution of the program
    return 0;
}

// Function to detect and draw any faces that is present in an image
void detect_and_draw( IplImage* img )
{

    // Create memory for calculations
    static CvMemStorage* storage = 0;

    // Create a new Haar classifier
    static CvHaarClassifierCascade* cascade = 0;

    int scale = 1;

    // Create a new image based on the input image
    IplImage* temp = cvCreateImage( cvSize(img->width/scale,img->height/scale), 8, 3 );

    // Create two points to represent the face locations
    CvPoint pt1, pt2;
    int i;

    // Load the HaarClassifierCascade
    cascade = (CvHaarClassifierCascade*)cvLoad( cascade_name, 0, 0, 0 );

    // Check whether the cascade has loaded successfully. Else report and error and quit
    if( !cascade )
    {
        fprintf( stderr, "ERROR: Could not load classifier cascade\n" );
        return;
    }

    // Allocate the memory storage
    storage = cvCreateMemStorage(0);

    // Create a new named window with title: result
    cvNamedWindow( "result", 1 );

    // Clear the memory storage which was used before
    cvClearMemStorage( storage );

    // Find whether the cascade is loaded, to find the faces. If yes, then:
    if( cascade )
    {

        // There can be more than one face in an image. So create a growable sequence of faces.
        // Detect the objects and store them in the sequence
        CvSeq* faces = cvHaarDetectObjects( img, cascade, storage,
                                            1.1, 2, CV_HAAR_DO_CANNY_PRUNING,
                                            cvSize(40, 40) );

        // Loop the number of faces found.
        for( i = 0; i < (faces ? faces->total : 0); i++ )
        {
           // Create a new rectangle for drawing the face
            CvRect* r = (CvRect*)cvGetSeqElem( faces, i );

            // Find the dimensions of the face,and scale it if necessary
            pt1.x = r->x*scale;
            pt2.x = (r->x+r->width)*scale;
            pt1.y = r->y*scale;
            pt2.y = (r->y+r->height)*scale;

            // Draw the rectangle in the input image
            cvRectangle( img, pt1, pt2, CV_RGB(255,0,0), 3, 8, 0 );
        }
    }

    // Show the image in the window named "result"
    cvShowImage( "result", img );

    // Release the temp image created.
    cvReleaseImage( &temp );
}