I am using opencv 2.410 to implement a project. My project allows to segment head from video sequence which get from camera. First, I detect the head region and then apply segmentation method for that ROI region. For high accurate segmentation, I have chosen Grabcut method. However, it is very slow. I only achieved about 2 frames/second (Although I used downsampling method). I have two questions:
1. Have any faster method than Grabcut which have similar accuracy? On other hands, Do we have any way to segment head region.
2. Could you see my code and give me some optimal way to make it faster?
Thank you in advance
#include <iostream>
#include <string>
#include <time.h>
//include opencv core
#include "opencv2\core\core.hpp"
#include "opencv2\contrib\contrib.hpp"
#include "opencv2\highgui\highgui.hpp"
#include "opencv2\objdetect\objdetect.hpp"
#include "opencv2\opencv.hpp"
//file handling
#include <fstream>
#include <sstream>
using namespace std;
using namespace cv;
//Functions
int VideoDisplay();
Mat GrabCut(Mat image);
const unsigned int BORDER = 5;
const unsigned int BORDER2 = BORDER + BORDER;
int main()
{
int value=VideoDisplay();
system("pause");
return 0;
}
Mat GrabCut(Mat image)
{
clock_t tStart_all = clock();
cv::Mat result; // segmentation result (4 possible values)
cv::Mat bgModel,fgModel; // the models (internally used)
// downsample the image
cv::Mat downsampled;
cv::pyrDown(image, downsampled, cv::Size(image.cols/2, image.rows/2));
cv::Rect rectangle(BORDER,BORDER,downsampled.cols-BORDER2,downsampled.rows-BORDER2);
clock_t tStart = clock();
// GrabCut segmentation
cv::grabCut(downsampled, // input image
result, // segmentation result
rectangle,// rectangle containing foreground
bgModel,fgModel, // models
1, // number of iterations
cv::GC_INIT_WITH_RECT); // use rectangle
printf("Time taken by GrabCut with downsampled image: %f s\n", (clock() - tStart)/(double)CLOCKS_PER_SEC);
// Get the pixels marked as likely foreground
cv::compare(result,cv::GC_PR_FGD,result,cv::CMP_EQ);
// upsample the resulting mask
cv::Mat resultUp;
cv::pyrUp(result, resultUp, cv::Size(result.cols*2, result.rows*2));
// Generate output image
cv::Mat foreground(image.size(),CV_8UC3,cv::Scalar(255,255,255));
image.copyTo(foreground,resultUp); // bg pixels not copied
return foreground;
}
int VideoDisplay(){
cout << "start recognizing..." << endl;
//lbpcascades/lbpcascade_frontalface.xml
string classifier = "C:/opencv/sources/data/haarcascades/haarcascade_frontalface_default.xml";
CascadeClassifier face_cascade;
string window = "Capture - face detection";
if (!face_cascade.load(classifier)){
cout << " Error loading file" << endl;
return -1;
}
VideoCapture cap(0);
//VideoCapture cap("C:/Users/lsf-admin/Pictures/Camera Roll/video000.mp4");
if (!cap.isOpened())
{
cout << "exit" << endl;
return -1;
}
//double fps = cap.get(CV_CAP_PROP_FPS);
//cout << " Frames per seconds " << fps << endl;
namedWindow(window, 1);
long count = 0;
int fps=0;
//Start and end times
time_t start,end;
//Start the clock
time(&start);
int counter=0;
while (true)
{
vector<Rect> faces;
Mat frame;
Mat graySacleFrame;
Mat original;
cap >> frame;
time(&end);
++counter;
double sec=difftime(end,start);
fps=counter/sec;
if (!frame.empty()){
//clone from original frame
original = frame.clone();
//convert image to gray scale and equalize
cvtColor(original, graySacleFrame, CV_BGR2GRAY);
//equalizeHist(graySacleFrame, graySacleFrame);
//detect face in gray image
face_cascade.detectMultiScale(graySacleFrame, faces, 1.1, 3, 0, cv::Size(90, 90));
//number of faces detected
//cout << faces.size() << " faces detected" << endl;
std::string frameset = std::to_string(fps);
std::string faceset = std::to_string(faces.size());
int width = 0, height = 0;
cv::Mat seg_grabcut;
//region of interest
for (int i = 0; i < faces.size(); i++)
{
//region of interest
Rect face_i = faces[i];
////crop the roi from grya image
//Mat face = graySacleFrame(face_i);
Mat crop = original(face_i);
////resizing the cropped image to suit to database image sizes
Mat face_resized;
cv::resize(crop, face_resized, Size(512,512), 1.0, 1.0, INTER_CUBIC);
//drawing green rectagle in recognize face
rectangle(original, face_i, CV_RGB(0, 255, 0), 1);
if(!face_resized.empty())
{
seg_grabcut=GrabCut(face_resized);
if (!seg_grabcut.empty())
{
imshow("segmented result", seg_grabcut);
}
}
}
putText(original, "Frames/Second: " + frameset, Point(30, 60), CV_FONT_HERSHEY_COMPLEX_SMALL, 1.0, CV_RGB(0, 255, 0), 1.0);
//display to the winodw
cv::imshow(window, original);
//cout << "model infor " << model->getDouble("threshold") << endl;
}
if (waitKey(30) >= 0) break;
}
}