Video gets stuck meanshift tracking opencv - c++

Question

I want to track any moving object using meanshift algorithm. For this I am first subtracting frames from background. Then erosion, dilation and smoothing is applied. In order to detect moving object, and to find its coordinates, I am using corner point detection.
Then I calculate mean of corner points, and pass these points to meanshift searching window. Now when object appears in screen, the program leaves corner point detection and enters meanshift tracking. It keeps running in meanshift until the object leaves the screen.
Now if object leaves the screen, I want to activate corner point detection again. For this, I take the program out of meanshift and jump back to corner point detection. The program is running fine but the problem is when it leaves meanshift and enters corner point detection again, it gets stuck for few seconds.
After that it runs smoothly. The problem occurs only during transition from meanshift to corner point detection. I don't know what could be the possible reason. Kindly tell me some solution.
Here is my code:
#include "highgui.h"
#include "cv.h"
#include "cxcore.h"
#include "cvaux.h"
#include <iostream>
using namespace std;
const int MAX_CORNERS = 500;
inline static void allocateOnDemand(IplImage** img, CvSize size, int depth, int channels) {
if (*img != NULL)
return;
*img = cvCreateImage(size, depth, channels);
if (*img == NULL) {
fprintf(stderr, "Error: Couldn't allocate image. Out of memory?\n");
exit(-1);
}
}
int main() {
CvCapture* capture = cvCaptureFromCAM(CV_CAP_V4L2);
IplImage* pFrame[10];
IplImage* bg;
IplImage* img_A;
IplImage* img_B;
IplImage* eig_image;
IplImage* tmp_image;
img_A = cvQueryFrame(capture);
CvSize img_sz = cvGetSize(img_A);
int c1 = 0, c2 = 0;
int xarr[40];
//A temporary replacement for background averaging
int j = 0;
for (j = 0; j < 10; j++) {
pFrame[j] = cvQueryFrame(capture);
cvWaitKey(200);
}
cvSaveImage("10.jpg", pFrame[9], 0); //saving the background
IplImage* imgA = cvCreateImage(cvGetSize(img_A), 8, 1);
IplImage* imgB = cvCreateImage(cvGetSize(img_A), 8, 1);
IplImage* imgB1 = cvCreateImage(cvGetSize(img_A), 8, 1);
IplImage* imgb = cvCreateImage(cvGetSize(img_A), 8, 1);
cvNamedWindow("LKpyr_OpticalFlow", CV_WINDOW_AUTOSIZE);
bg = cvLoadImage("10.jpg", CV_LOAD_IMAGE_GRAYSCALE); //loading the saved background
int flag = 0;
int index = 0;
char keypress;
bool quit = false;
CvConnectedComp*out = new CvConnectedComp(); //output window for meanshift
int win_size = 25; //window size for corner point detection
int x1 = 0;
int y1 = 0;
int x;
int y;
int cc;
line3:
while (quit == false) { //line3:
IplImage* imgC = cvCreateImage(cvGetSize(img_A), 8, 1); //creating output image
cvZero(imgC);
img_B = cvQueryFrame(capture);
imgC = cvQueryFrame(capture);
// line3:
int corner_count = MAX_CORNERS; //total no of corners found in frame
cvCvtColor(img_B, imgb, CV_BGR2GRAY);
//line3:
CvPoint2D32f* cornersA = new CvPoint2D32f[MAX_CORNERS];
CvPoint2D32f* cornersB = new CvPoint2D32f[MAX_CORNERS];
if (index % 2 == 0) {
cvSub(imgb, bg, imgB, NULL); //background subtraction and stuff
cvErode(imgB, imgB, NULL, 4);
cvDilate(imgB, imgB, 0, 2);
cvSmooth(imgB, imgB, 0, 1);
cvThreshold(imgB, imgB, 50, 255, CV_THRESH_BINARY);
//line3:
if (flag == 1) goto line1; //Go to Meanshift
allocateOnDemand(&eig_image, img_sz, IPL_DEPTH_32F, 1);
allocateOnDemand(&tmp_image, img_sz, IPL_DEPTH_32F, 1);
cvCvtColor(img_A, imgA, CV_BGR2GRAY);
//line3:
cvGoodFeaturesToTrack(imgB, eig_image, tmp_image, cornersA, &
corner_count, 0.05, 5.0, 0, 3, 0, 0.04); //detects corners and no of corners stored in corner_count
cvFindCornerSubPix(imgB, cornersA, corner_count, cvSize(12, 12),
cvSize(-1, -1), cvTermCriteria(CV_TERMCRIT_ITER |
CV_TERMCRIT_EPS, 20, 0.03));
CvPoint p0;
CvPoint p1;
CvPoint acc;
cc = corner_count + 20;
acc.x = 0;
acc.y = 0;
for (int i = 0; i < corner_count; i++) {
p0 = cvPoint(cvRound(cornersA[i].x), cvRound(cornersA[i].y));
p1 = cvPoint(cvRound(cornersB[i].x), cvRound(cornersB[i].y));
acc.x = acc.x + p0.x; //calculating mean of corner points
acc.y = acc.y + p0.y;
}
delete[] cornersA;
delete[] cornersB;
cout << "Corner Count is" << corner_count << endl;
cout << "Flag status: " << flag << endl;
if (corner_count > 0) {
flag = 1;
cvWaitKey(20);
}
x1 = cvRound(acc.x / (corner_count + 1));
y1 = cvRound(acc.y / (corner_count + 1));
cout << "x is " << x1 << " y is " << y1 << endl;
cout << "Flag status: " << flag << endl;
x = x1;
y = y1;
if (flag == 0) goto line2; //Go back to Corner Point detection
line1: CvRect window = cvRect(x, y, 80, 90); //Creates window for meanshift algo
cvMeanShift(imgB, window, cvTermCriteria(CV_TERMCRIT_EPS |
CV_TERMCRIT_ITER, 200, 1), out);
window = out->rect;
x = out->rect.x;
y = out->rect.y;
cout << "Now x is " << x << " y is " << y << endl;
cout << "Flag status: " << flag << endl;
if (out->area > 200) {
cvRectangle(imgC, cvPoint(x + 50, y + 100), cvPoint(x - 20, y -
90), cvScalar(0, 0, 255), 3, 8, 0);
} else {}
xarr[c1] = x;
c1++;
if (c1 > 39) c1 = 0;
if (xarr[0] == xarr[39]) {
c2 = 1;
cout << "c2 is now " << c2 << endl;
}
}
if (x == 0 || y == 0 || x < 7 || x > 572 || c2 == 1) {
flag = 0;
c2 = 0;
goto line3;
break;
}
line2: cvShowImage("LKpyr_OpticalFlow", imgC);
keypress = cvWaitKey(20);
// Set the flag to quit if escape was pressed
if (keypress == 27) {
quit = true;
}
//index++;
} //end of while
return 0;
}