how to save identical faces only once - c++

Question

I am doing a project on face detection from surveillance cameras.Now I am at the stage of face detection and I can detect faces from each frame.After detecting the face I need store that face to local folder.Now I can save each face in the specified folder.
Problem Now it is saving every faces,but I need to save identical faces only once.That means if saved one face as a jpeg image and when face detection progress again the same face is coming, so this time I don't want to save that particular face.
This is my code:
#include <cv.h>
#include <highgui.h>
#include <time.h>
#include <stdio.h>
using namespace std;
int ct=1;
int ct1=0;
IplImage *frame;
int frames;
void facedetect(IplImage* image);
void saveImage(IplImage *img,char *ex);
IplImage* resizeImage(const IplImage *origImg, int newWidth,int newHeight, bool keepAspectRatio);
const char* cascade_name="haarcascade_frontalface_default.xml";
int k=1;
int main(int argc, char** argv)
{
CvCapture *capture=cvCaptureFromFile("Arnab Goswami on Pepper spary rajagopal Complete NewsHour Debate (Mobile).3gp");
int count=1;
while(1)
{
frame = cvQueryFrame(capture);
if(count%30==0)
{
facedetect(frame);
}
count++;
}
cvReleaseCapture(&capture);
return 0;
}
void facedetect(IplImage* image)
{
ct1++;
cvNamedWindow("output");
int j=0,i,count=0,l=0,strsize;
char numstr[50];
int arr[100],arr1[100];
CvPoint ul,lr,w,h,ul1,lr1;
CvRect *r;
//int i=0;
IplImage* image1;IplImage* tmpsize;IplImage* reimg;
CvHaarClassifierCascade* cascade=(CvHaarClassifierCascade*) cvLoad(cascade_name);
CvMemStorage* storage=cvCreateMemStorage(0);
const char *extract;
if(!cascade)
{
cout<<"Coulid not load classifier cascade"<<endl;
}
if(cascade)
{
CvSeq*faces=cvHaarDetectObjects(image,cascade,storage,1.1,1,CV_HAAR_DO_CANNY_PRUNING,cvSize(10,10));
//function used for detecting faces.o/p is list of detected faces.
for(int i=0;i<(faces ? faces->total : 0);i++)
{
string s1="im",re,rename,ex=".jpeg";
sprintf(numstr, "%d", k);
re = s1 + numstr;
rename=re+ex;
char *extract1=new char[rename.size()+1];
extract1[rename.size()]=0;
memcpy(extract1,rename.c_str(),rename.size());
//Copies the values of rename.size from the location pointed by source //(rename.c_str)directly to the memory block pointed by destination(extract).
strsize=rename.size();
r=(CvRect*) cvGetSeqElem(faces,i);//draw rectangle outline around each image.
ul.x=r->x;
ul.y=r->y;
w.x=r->width;
h.y=r->height;
lr.x=(r->x + r->width);
lr.y=(r->y + r->height);
cvSetImageROI(image,cvRect(ul.x,ul.y,w.x,h.y));
image1=cvCreateImage(cvGetSize(image),image->depth,image->nChannels);
cvCopy(image, image1, NULL);
reimg=resizeImage(image1, 40, 40, true);
saveImage(reimg,extract1);
cvResetImageROI(image);
cvRectangle(image,ul,lr,CV_RGB(1,255,0),3,8,0);
j++,count++;
k++;
cout<<"frame"<<ct1<<" "<<"face"<<ct<<":"<<"x: "<<ul.x<<endl;
cout<<"frame"<<ct1<<" "<<"face"<<ct<<":"<<"y: "<<ul.y<<endl;
cout<<""<<endl;
ct++;
//cvShowImage("output",image);
}
//return image;
//cvNamedWindow("output");//creating a window.
cvShowImage("output",image);//showing resized image.
cvWaitKey(0);
}
}
void saveImage(IplImage *img,char *ex)
{
int i=0;
char path[255]="/home/athira/Image/OutputImage";
char *ext[200];
char buff[1000];
ext[i]=ex;
sprintf(buff,"%s/%s",path,ext[i]);//copy ext[i] to buff
strcat(path,buff);//concat path & buff
cvSaveImage(buff,img);
i++;
}

Answer 1

You are using the haar feature-based cascade classifier for object detection. As far as i know these xml files are only trained to detect the specific objects based on hundreds of evaluated pictures (see cascade classifier training).
So to compare saved images you will need another "detection" mode, because you have to compare if two faces are identical with respect to the view angle and so on (keyword: biometric data).
The keyword you're looking for is "face recognition" i think. Just build up a database based on your detected faces and use them for face recognition after that.
Edit:
Another maybe helpful link: www.shervinemami.info/faceRecognition.html

Answer 2

If I understood correctly, what you want is to detect faces in one frame, save a thumbnail of this face. Then, in the following frame, you want to detect faces again but only save the thumbnails for those that were not present in the first frame.
This problem is hard, because the faces captured in a video always change from one frame to the next. This is due to noise in the images, to the fact that the persons may be moving, etc. As a consequence, no two faces are ever identical in a surveillance video.
Hence, in order to achieve what you asked, you need to determine if the face you are considering has already been observed in previous frames. In its general form, this problem is not obvious one and is still the topic of a lot of research related to biometrics, pedestrian tracking and re-identification, etc. Therefore, you will have a hard time to achieve 100% effectiveness in detecting that a given face has already been observed.
However, if can accept a method that is not 100% effective, you could try the following approach:
Detect faces F0i in frame 0, with associated image position (x0i, y0i), and store the thumbnails
Compute sparse optical-flow (e.g. using KLT, see this link) on the positions (xn-1i, yn-1i) of the faces in previous frame n-1, in order to estimate their positions (xxni, yyni) in the current frame n.
Detect faces F0i in the current frame n, with associated image position (xni, yni), and save only the thumbnail of those which are not close to one of the predicted positions (xxni, yyni).
Increment n and repeat steps 2-3 using the next frame.
This is a simple algorithm using tracking to determine if a given face was already observed previously. It should be easier to implement than biometrics-based approaches, and also probably more appropriate in the context of video surveillance. However, it is not a 100% accurate, due to the limited effectivity of the optical-flow estimation and of the face detector.