Face features detection with OpenCV

Object detection proposed by Paul Viola was implemented in OpenCV. We also can find some classifiers (working with Haar-like features) in OpenCV such as frontal face, profile face, eyes, nose and mouth. Each classifier is trained with multiple sample views of a particular object in the same size including positive images and negative images.
In this post, we will use built-in OpenCV functions to detect some features on the face. First, we will detect all faces that are available in an image. After that, on each detected face, we will apply object detection for eyes, nose and mouth. As we know, human faces are rigid object and eyes, nose and mouth are located on particular region of the face. We can localize those features by setting "Region Of Interest" on each face to reduce calculation.

Here is the code

#include <iostream>
#include "stdio.h"
#include "opencv2/opencv.hpp"

using namespace std;
using namespace cv;

CvHaarClassifierCascade *cascade_f;
CvHaarClassifierCascade *cascade_e;
CvHaarClassifierCascade *cascade_n;
CvHaarClassifierCascade *cascade_m;
CvMemStorage   *storage;

#define NUM_OF_FEATURES 5

CvPoint2D32f frontal_frame_features[NUM_OF_FEATURES];

int detectFaces(IplImage *img, CvRect *face);
int detectFaceFeatures(IplImage *img, CvRect *face);
int tracking();

static const double pi = 3.14159265358979323846;

int main(int argc, char** argv)
{
    IplImage *img;
 const char *file1 = "C:/c-dev/OpenCV-2.2.0/data/haarcascades/haarcascade_frontalface_alt.xml";
    const char *file2 = "C:/c-dev/OpenCV-2.2.0/data/haarcascades/haarcascade_eye.xml";
 const char *file3 = "C:/c-dev/OpenCV-2.2.0/data/haarcascades/haarcascade_mcs_nose.xml";
 const char *file4 = "C:/c-dev/OpenCV-2.2.0/data/haarcascades/haarcascade_mcs_mouth.xml";

 cascade_f = (CvHaarClassifierCascade*)cvLoad(file1, 0, 0, 0);
    cascade_e = (CvHaarClassifierCascade*)cvLoad(file2, 0, 0, 0);
    cascade_n = (CvHaarClassifierCascade*)cvLoad(file3, 0, 0, 0);
    cascade_m = (CvHaarClassifierCascade*)cvLoad(file4, 0, 0, 0);

    /* setup memory storage, needed by the object detector */
    storage = cvCreateMemStorage(0);

    /* load image */
    img = cvLoadImage("lena.jpg", CV_LOAD_IMAGE_COLOR);

    assert(cascade_f && cascade_e && storage);

 const char* name = "Features-Detection";
    cvNamedWindow(name, 1);

 Mat frame = img;
 CvRect face;
 if (detectFaces(img, &face)) {
  if(detectFaceFeatures(img, &face)) {
   cout << "Features detected" << endl;
  }
 }
 cvShowImage(name, img);
 cvWaitKey(0);
    cvDestroyWindow(name);
    cvReleaseImage(&img);
    cvClearMemStorage(storage);

    return 0;
}

int detectFaces(IplImage *img, CvRect *face) {
    /* detect faces */
 CvSeq *faces = cvHaarDetectObjects(
            img, cascade_f, storage,
            1.1, 2, CV_HAAR_DO_CANNY_PRUNING, cvSize( 50, 50 ) );

 if (faces->total == 0) {
  return 0;
 }
 CvRect* _face = (CvRect*)cvGetSeqElem(faces, 0);
 face->x = _face->x;
 face->y = _face->y;
 face->width = _face->width;
 face->height = _face->height;
 return 1;
}

int detectFaceFeatures(IplImage *img, CvRect *face)
{
 int i;
 bool hasEyes = false;
 bool hasNose = false;
 bool hasMouth = false;
 cvRectangle(img,
    cvPoint(face->x, face->y),
    cvPoint(face->x + face->width, face->y + face->height),
    CV_RGB(255, 0, 0), 1, 8, 0);

    /* Set the Region of Interest*/
 CvRect eyeROI = cvRect(face->x, face->y + (face->height/5.5), face->width, face->height/3.0);
 CvRect noseROI = cvRect(face->x, face->y + (face->height/2.5), face->width, face->height/3.0);
 CvRect mouthROI = cvRect(face->x, face->y + (face->height/1.5), face->width, face->height/2.5);

 CvRect *r;
    /* detect eyes */
 cvSetImageROI(img, eyeROI);
 CvSeq* eyes = cvHaarDetectObjects(
           img, cascade_e, storage,
           1.15, 3, 0, cvSize(25, 15));
 cvResetImageROI(img);
 /* detect nose */
 cvSetImageROI(img, noseROI);
 CvSeq* noses = cvHaarDetectObjects(
           img, cascade_n, storage,
           1.1, 3, 0, cvSize(25, 15));
 cvResetImageROI(img);
 /* detect Mouth */
 cvSetImageROI(img, mouthROI);
 CvSeq* mouths = cvHaarDetectObjects(
            img, cascade_m, storage,
            1.1, 3, 0, Size(30, 30));
 cvResetImageROI(img);
 /* draw a rectangle for each eye found */
 for( i = 0; i < (eyes ? eyes->total : 0); i++ ) {
  r = (CvRect*)cvGetSeqElem( eyes, i );
  int x1 = r->x + eyeROI.x;
  int y1 = r->y + eyeROI.y;
  int x2 = x1 + r->width;
  int y2 = y1 + r->height;
  int xc = (x1 + x2)/2;
  int yc = (y1 + y2)/2;
  cvRectangle(img,
     cvPoint(x1, y1),
     cvPoint(x2, y2),
     CV_RGB(255, 0, 0), 1, 8, 0);
  cvCircle(img, cvPoint(xc, yc), 2, CV_RGB(255,0,0), 2, 8, 0);
  float fX = xc;
  float fY = yc;
  frontal_frame_features[i] = cvPoint2D32f(fX,fY);
  if (i==1) {
   hasEyes = true;
  }
 }
 /* draw a rectangle for each nose found */
 for( i = 0; i < (noses ? noses->total : 0); i++ ) {
  r = (CvRect*)cvGetSeqElem( noses, i );
  int x1 = r->x + noseROI.x;
  int y1 = r->y + noseROI.y;
  int x2 = x1 + r->width;
  int y2 = y1 + r->height;
  int xc = (x1 + x2)/2;
  int yc = (y1 + y2)/2;
  cvRectangle(img,
     cvPoint(x1, y1),
     cvPoint(x2, y2),
     CV_RGB(0, 255, 0), 1, 8, 0);
  cvCircle(img, cvPoint(xc, yc), 2, CV_RGB(255,0,0), 2, 8, 0);
  hasNose = true;
  float fX = xc;
  float fY = yc;
  frontal_frame_features[2] = cvPoint2D32f(fX,fY);
 }
 /* draw a rectangle for each mouth found */
 for( i = 0; i < (mouths ? mouths->total : 0); i++ ) {
  int margin_left = 10;
  int margin_right = 0;
  r = (CvRect*)cvGetSeqElem( mouths, i );
  int x1 = r->x + mouthROI.x;
  int y1 = r->y + mouthROI.y;
  int x2 = x1 + r->width;
  int y2 = y1 + r->height;
  int x1c = x1 + margin_left;
  int y1c = (y1 + y2)/2;
  int x2c = x2 - margin_right;
  int y2c = (y1 + y2)/2 - 5;
  cvRectangle(img,
     cvPoint(x1, y1),
     cvPoint(x2, y2),
     CV_RGB(0, 0, 255), 1, 8, 0);
  cvCircle(img, cvPoint(x1c, y1c), 2, CV_RGB(255,0,0), 2, 8, 0);
  cvCircle(img, cvPoint(x2c, y2c), 2, CV_RGB(255,0,0), 2, 8, 0);
  hasMouth = true;
  frontal_frame_features[3] = cvPoint2D32f(x1c,y1c);
  frontal_frame_features[4] = cvPoint2D32f(x2c,y2c);
 }
 return (hasEyes && hasNose && hasMouth)?1:0;
}

And result: