I am trying a very simple program to detect faces in a webcam feed. I am noticing that the faces are detected well when my face is in the centre of the frame. Whenever I move a bit to the sides, the face detector either completely misses my face or gives no detection. Is this bias because of the way I am using the function (code appended) or is it an inherent bias in the HAAR Classifiers? Note that in either case (my face being in the approximate centre of the frame or my face being somewhere near the boundaries), my face is completely visible, i.e so side profiles/or cutting of the face.
//A live face detector Program. Takes feed from the camera and detects face in the given frame
#include<opencv2/opencv.hpp>
#include<iostream>
#include<vector>
#include"opencv2/video/video.hpp"
using namespace cv;
using namespace std;
int main(){
cv::Mat frame;
cv::VideoCapture cap(0);
cv::namedWindow("Frame");
do{
cap >> frame;
Rect r1,r2;
vector<Rect> faces1,faces2;
CascadeClassifier cascade1;
CascadeClassifier cascade2;
//cascade1.load("C:/opencv2.4.9/sources/data/lbpcascades/lbpcascade_frontalface.xml");
cascade1.load("C:/opencv2.4.9/sources/data/haarcascades/haarcascade_frontalface_alt2.xml");
cascade2.load("C:/opencv2.4.9/sources/data/lbpcascades/lbpcascade_profileface.xml");
cascade1.detectMultiScale(frame, faces1,1.05, 6, CV_HAAR_FIND_BIGGEST_OBJECT, Size(0, 0));
cascade2.detectMultiScale(frame, faces2,1.05, 6, CV_HAAR_FIND_BIGGEST_OBJECT, Size(0, 0));
if (faces1.size()!=0){
cout << "face1 found";
r1 = faces1[0];
}
if (faces2.size()!=0){
cout << "face2 found";
r2 = faces2[0];
}
rectangle(frame, Point(r1.y,r1.x), Point(r1.y+r1.height,r1.x+r1.width), Scalar(0,255,0),2, 8);
rectangle(frame, Point(r2.y,r2.x), Point(r2.y+r2.height,r2.x+r2.width), Scalar(255,0,0),2, 8);
imshow("Frame",frame);
}while(waitKey(30) < 0);
cap.release();
return 0;
}
Also here: http://stackoverflow.com/questions/24691701/why-does-detectmultiscale-detect-faces-only-when-they-are-close-to-the-centre-of