Opencv C++ Tutorial of Face(object) Detection Using Haar Cascade

This OpenCV C++ Tutorial is about doing Face(object) Detection Using Haar Cascade.
The Steps of Doing Object Detection (Here it is face) using Haar Cascade are:-

1. Load the Input Image.
2. Load the Haar Cascade File (here it is haarcascade_frontalface_alt2.xml)
   Normally it is an XML file.
3. Detect the Objects(here it is face) using detectMultiScale()
4. Create ROI over the detected Objects(face).
   i.e. Draw a Rectangle or a Circle over the detected objects to mark them.
5. Show the Output i.e. Marked Objects(faces)

Syntax:
C++: void CascadeClassifier::detectMultiScale(const Mat& image, vector& objects, double scaleFactor=1.1, int minNeighbors=3, int flags=0, Size minSize=Size(), Size maxSize=Size())
Parameters:

• image – Matrix of the type CV_8U containing an image where objects are detected.
• objects – Vector of rectangles where each rectangle contains the detected object.
• scaleFactor – Parameter specifying how much the image size is reduced at each image scale.
• minNeighbors – Parameter specifying how many neighbors each candidate rectangle should have to retain it.This parameter will affect the quality of the detected faces: higher value results in less detections but with higher quality.
• flags – Parameter with the same meaning for an old cascade as in the function cvHaarDetectObjects. It is not used for a new cascade.
• minSize – Minimum possible object size. Objects smaller than that are ignored.
• maxSize – Maximum possible object size. Objects larger than that are ignored.

//Opencv C++ Example on Face Detection Using Haar Cascade
 
/*We can similarly train our own Haar Classifier and Detect any object which we want
Only Thing is we need to load our Classifier in palce of cascade_frontalface_alt2.xml */
 
#include "opencv2/objdetect/objdetect.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/imgproc/imgproc.hpp"
  
#include <iostream>
#include <stdio.h>
  
using namespace std;
using namespace cv;
  
int main( )
{
    Mat image;
    image = imread("C:\\Users\\arjun\\Desktop\\opencv-face-haarcascade-input.jpg", CV_LOAD_IMAGE_COLOR);  
    namedWindow( "window1", 1 );   imshow( "window1", image );
  
    // Load Face cascade (.xml file)
    CascadeClassifier face_cascade;
    face_cascade.load( "D:\\opencv2410\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml" );

 if(face_cascade.empty())
// if(!face_cascade.load("D:\\opencv2410\\sources\\data\\haarcascades\\haarcascade_frontalface_alt.xml"))
 {
  cerr<<"Error Loading XML file"<<endl;
  return 0;
 }
 
    // Detect faces
    std::vector<Rect> faces;
    face_cascade.detectMultiScale( image, faces, 1.1, 2, 0|CV_HAAR_SCALE_IMAGE, Size(30, 30) );
  
    // Draw circles on the detected faces
    for( int i = 0; i < faces.size(); i++ )
    {
        Point center( faces[i].x + faces[i].width*0.5, faces[i].y + faces[i].height*0.5 );
        ellipse( image, center, Size( faces[i].width*0.5, faces[i].height*0.5), 0, 0, 360, Scalar( 255, 0, 255 ), 4, 8, 0 );
    }
      
    imshow( "Detected Face", image );
      
    waitKey(0);                   
    return 0;
}

Input:-

Output:-