OpenCV: Problems with Stereo Rectification (using sample code from book) - image-processing

Question

So I am having problems with OpenCV. I used the sample code from the book, "Learning OpenCV". I got the code to compute all of the intrinsics and extrinsics of the two cameras, but when I go to Remap the images, all I get is a blank image. I use 6 images from both cameras, with a 9x6 chessboard. The input file alternates with left and right images (the lr=i%2 made me think that...).
Below is my code. I only added the cvRemap() function towards the end.
#undef _GLIBCXX_DEBUG
#include <opencv\cv.h>
#include <opencv\cxmisc.h>
#include <opencv\highgui.h>
#include <vector>
#include <string>
#include <algorithm>
#include <stdio.h>
#include <ctype.h>
#include <Windows.h>
using namespace std;
//
// Given a list of chessboard images, the number of corners (nx, ny)
// on the chessboards, and a flag: useCalibrated for calibrated (0) or
// uncalibrated (1: use cvStereoCalibrate(), 2: compute fundamental
// matrix separately) stereo. Calibrate the cameras and display the
// rectified results along with the computed disparity images.
//
static void
StereoCalib(const char* imageList, int useUncalibrated)
{
IplImage* L_img1 = cvLoadImage("bad1.bmp");
IplImage* R_img1 = cvLoadImage("good1.bmp");
IplImage* fixed_L = cvCloneImage(L_img1);
IplImage* fixed_R = cvCloneImage(R_img1);
CvRect roi1, roi2;
int nx = 0, ny = 0;
int displayCorners = 1;
int showUndistorted = 1;
bool isVerticalStereo = false; //OpenCV can handle left-right
//or up-down camera arrangements
const int maxScale = 1;
const float squareSize = 1.f; //Set this to your actual square size
FILE* f = fopen(imageList, "rt");
int i, j, lr, nframes = 0, n, N = 0;
vector<string> imageNames[2];
vector<CvPoint3D32f> objectPoints;
vector<CvPoint2D32f> points[2];
vector<CvPoint2D32f> temp_points[2];
vector<int> npoints;
//vector<uchar> active[2];
int is_found[2] = {0, 0};
vector<CvPoint2D32f> temp;
CvSize imageSize = {0,0};
// ARRAY AND VECTOR STORAGE:
double M1[3][3], M2[3][3], D1[5], D2[5];
double R[3][3], T[3], E[3][3], F[3][3];
double Q[4][4];
CvMat _M1 = cvMat(3, 3, CV_64F, M1 );
CvMat _M2 = cvMat(3, 3, CV_64F, M2 );
CvMat _D1 = cvMat(1, 5, CV_64F, D1 );
CvMat _D2 = cvMat(1, 5, CV_64F, D2 );
CvMat _R = cvMat(3, 3, CV_64F, R );
CvMat _T = cvMat(3, 1, CV_64F, T );
CvMat _E = cvMat(3, 3, CV_64F, E );
CvMat _F = cvMat(3, 3, CV_64F, F );
CvMat _Q = cvMat(4, 4, CV_64FC1, Q);
char buf[1024];
if( displayCorners )
cvNamedWindow( "corners", 1 );
// READ IN THE LIST OF CHESSBOARDS:
if( !f )
{
fprintf(stderr, "can not open file %s\n", imageList );
Sleep(2000);
return;
}
if( !fgets(buf, sizeof(buf)-3, f) || sscanf(buf, "%d%d", &nx, &ny) != 2 )
return;
n = nx*ny;
temp.resize(n);
temp_points[0].resize(n);
temp_points[1].resize(n);
for(i=0;;i++)
{
int count = 0, result=0;
lr = i % 2;
vector<CvPoint2D32f>& pts = temp_points[lr];//points[lr];
if( !fgets( buf, sizeof(buf)-3, f ))
break;
size_t len = strlen(buf);
while( len > 0 && isspace(buf[len-1]))
buf[--len] = '\0';
if( buf[0] == '#')
continue;
IplImage* img = cvLoadImage( buf, 0 );
if( !img )
break;
imageSize = cvGetSize(img);
imageNames[lr].push_back(buf);
//FIND CHESSBOARDS AND CORNERS THEREIN:
for( int s = 1; s <= maxScale; s++ )
{
IplImage* timg = img;
if( s > 1 )
{
timg = cvCreateImage(
cvSize(img->width*s,img->height*s),
img->depth, img->nChannels
);
cvResize( img, timg, CV_INTER_CUBIC );
}
result = cvFindChessboardCorners(
timg, cvSize(nx, ny),
&temp[0], &count,
CV_CALIB_CB_ADAPTIVE_THRESH |
CV_CALIB_CB_NORMALIZE_IMAGE
);
if( timg != img )
cvReleaseImage( &timg );
if( result || s == maxScale )
for( j = 0; j < count; j++ )
{
temp[j].x /= s;
temp[j].y /= s;
}
if( result )
break;
}
if( displayCorners )
{
printf("%s\n", buf);
IplImage* cimg = cvCreateImage( imageSize, 8, 3 );
cvCvtColor( img, cimg, CV_GRAY2BGR );
cvDrawChessboardCorners(
cimg, cvSize(nx, ny), &temp[0],
count, result
);
IplImage* cimg1 = cvCreateImage(cvSize(640, 480), IPL_DEPTH_8U, 3);
cvResize(cimg, cimg1);
cvShowImage( "corners", cimg1 );
cvReleaseImage( &cimg );
cvReleaseImage( &cimg1 );
int c = cvWaitKey(1000);
if( c == 27 || c == 'q' || c == 'Q' ) //Allow ESC to quit
exit(-1);
}
else
putchar('.');
//N = pts.size();
//pts.resize(N + n, cvPoint2D32f(0,0));
//active[lr].push_back((uchar)result);
is_found[lr] = result > 0 ? 1 : 0;
//assert( result != 0 );
if( result )
{
//Calibration will suffer without subpixel interpolation
cvFindCornerSubPix(
img, &temp[0], count,
cvSize(11, 11), cvSize(-1,-1),
cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 30, 0.01)
);
copy( temp.begin(), temp.end(), pts.begin() );
}
cvReleaseImage( &img );
if(lr)
{
if(is_found[0] == 1 && is_found[1] == 1)
{
assert(temp_points[0].size() == temp_points[1].size());
int current_size = points[0].size();
points[0].resize(current_size + temp_points[0].size(), cvPoint2D32f(0.0, 0.0));
points[1].resize(current_size + temp_points[1].size(), cvPoint2D32f(0.0, 0.0));
copy(temp_points[0].begin(), temp_points[0].end(), points[0].begin() + current_size);
copy(temp_points[1].begin(), temp_points[1].end(), points[1].begin() + current_size);
nframes++;
printf("Pair successfully detected...\n");
}
is_found[0] = 0;
is_found[1] = 0;
}
}
fclose(f);
printf("\n");
// HARVEST CHESSBOARD 3D OBJECT POINT LIST:
objectPoints.resize(nframes*n);
for( i = 0; i < ny; i++ )
for( j = 0; j < nx; j++ )
objectPoints[i*nx + j] = cvPoint3D32f(i*squareSize, j*squareSize, 0);
for( i = 1; i < nframes; i++ )
copy(
objectPoints.begin(), objectPoints.begin() + n,
objectPoints.begin() + i*n
);
npoints.resize(nframes,n);
N = nframes*n;
CvMat _objectPoints = cvMat(1, N, CV_32FC3, &objectPoints[0] );
CvMat _imagePoints1 = cvMat(1, N, CV_32FC2, &points[0][0] );
CvMat _imagePoints2 = cvMat(1, N, CV_32FC2, &points[1][0] );
CvMat _npoints = cvMat(1, npoints.size(), CV_32S, &npoints[0] );
cvSetIdentity(&_M1);
cvSetIdentity(&_M2);
cvZero(&_D1);
cvZero(&_D2);
// CALIBRATE THE STEREO CAMERAS
printf("Running stereo calibration ...");
fflush(stdout);
cvStereoCalibrate(
&_objectPoints, &_imagePoints1,
&_imagePoints2, &_npoints,
&_M1, &_D1, &_M2, &_D2,
imageSize, &_R, &_T, &_E, &_F,
cvTermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 100, 1e-5),
CV_CALIB_FIX_ASPECT_RATIO +
CV_CALIB_ZERO_TANGENT_DIST +
CV_CALIB_SAME_FOCAL_LENGTH +
CV_CALIB_FIX_K3
);
printf(" done\n");
// CALIBRATION QUALITY CHECK
// because the output fundamental matrix implicitly
// includes all the output information,
// we can check the quality of calibration using the
// epipolar geometry constraint: m2^t*F*m1=0
vector<CvPoint3D32f> lines[2];
points[0].resize(N);
points[1].resize(N);
_imagePoints1 = cvMat(1, N, CV_32FC2, &points[0][0] );
_imagePoints2 = cvMat(1, N, CV_32FC2, &points[1][0] );
lines[0].resize(N);
lines[1].resize(N);
CvMat _L1 = cvMat(1, N, CV_32FC3, &lines[0][0]);
CvMat _L2 = cvMat(1, N, CV_32FC3, &lines[1][0]);
//Always work in undistorted space
cvUndistortPoints(
&_imagePoints1, &_imagePoints1,
&_M1, &_D1, 0, &_M1
);
cvUndistortPoints(
&_imagePoints2, &_imagePoints2,
&_M2, &_D2, 0, &_M2
);
cvComputeCorrespondEpilines( &_imagePoints1, 1, &_F, &_L1 );
cvComputeCorrespondEpilines( &_imagePoints2, 2, &_F, &_L2 );
double avgErr = 0;
for( i = 0; i < N; i++ )
{
double err =
fabs(
points[0][i].x*lines[1][i].x +
points[0][i].y*lines[1][i].y + lines[1][i].z
) +
fabs(
points[1][i].x*lines[0][i].x +
points[1][i].y*lines[0][i].y + lines[0][i].z
);
avgErr += err;
}
printf( "avg err = %g\n", avgErr/(nframes*n) );
// save intrinsic parameters
CvFileStorage* fstorage = cvOpenFileStorage("intrinsics.yml", NULL, CV_STORAGE_WRITE);
cvWrite(fstorage, "M1", &_M1);
cvWrite(fstorage, "D1", &_D1);
cvWrite(fstorage, "M2", &_M2);
cvWrite(fstorage, "D2", &_D2);
cvReleaseFileStorage(&fstorage);
//COMPUTE AND DISPLAY RECTIFICATION
if( showUndistorted )
{
CvMat* mx1 = cvCreateMat( imageSize.height, imageSize.width, CV_32F );
CvMat* my1 = cvCreateMat( imageSize.height, imageSize.width, CV_32F );
CvMat* mx2 = cvCreateMat( imageSize.height, imageSize.width, CV_32F );
CvMat* my2 = cvCreateMat( imageSize.height, imageSize.width, CV_32F );
CvMat* img1r = cvCreateMat( imageSize.height, imageSize.width, CV_8U );
CvMat* img2r = cvCreateMat( imageSize.height, imageSize.width, CV_8U );
CvMat* disp = cvCreateMat( imageSize.height, imageSize.width, CV_16S );
double R1[3][3], R2[3][3], P1[3][4], P2[3][4];
CvMat _R1 = cvMat(3, 3, CV_64F, R1);
CvMat _R2 = cvMat(3, 3, CV_64F, R2);
// IF BY CALIBRATED (BOUGUET'S METHOD)
if( useUncalibrated == 0 )
{
CvMat _P1 = cvMat(3, 4, CV_64F, P1);
CvMat _P2 = cvMat(3, 4, CV_64F, P2);
cvStereoRectify(
&_M1, &_M2, &_D1, &_D2, imageSize,
&_R, &_T,
&_R1, &_R2, &_P1, &_P2, &_Q,
CV_CALIB_ZERO_DISPARITY,
1, imageSize, &roi1, &roi2
);
CvFileStorage* file = cvOpenFileStorage("extrinsics.yml", NULL, CV_STORAGE_WRITE);
cvWrite(file, "R", &_R);
cvWrite(file, "T", &_T);
cvWrite(file, "R1", &_R1);
cvWrite(file, "R2", &_R2);
cvWrite(file, "P1", &_P1);
cvWrite(file, "P2", &_P2);
cvWrite(file, "Q", &_Q);
cvReleaseFileStorage(&file);
isVerticalStereo = fabs(P2[1][3]) > fabs(P2[0][3]);
if(!isVerticalStereo)
roi2.x += imageSize.width;
else
roi2.y += imageSize.height;
//Precompute maps for cvRemap()
cvNamedWindow( "Original" );
cvNamedWindow( "Fixed" );
cvInitUndistortRectifyMap(&_M1,&_D1,&_R1,&_P1,mx1,my1);
cvInitUndistortRectifyMap(&_M2,&_D2,&_R2,&_P2,mx2,my2);
cvRemap(R_img1, fixed_R, mx2, my2);
cvShowImage("Original", R_img1);
cvShowImage("Fixed", fixed_R);
while(1){
int c = cvWaitKey(15);
if(c == 'p') {
c = 0;
while(c != 'p' && c != 27) {
c = cvWaitKey(250);
}
}
if(c == 27)
break;
}// end while
}
//OR ELSE HARTLEY'S METHOD
else if( useUncalibrated == 1 || useUncalibrated == 2 )
// use intrinsic parameters of each camera, but
// compute the rectification transformation directly
// from the fundamental matrix
{
double H1[3][3], H2[3][3], iM[3][3];
CvMat _H1 = cvMat(3, 3, CV_64F, H1);
CvMat _H2 = cvMat(3, 3, CV_64F, H2);
CvMat _iM = cvMat(3, 3, CV_64F, iM);
//Just to show you could have independently used F
if( useUncalibrated == 2 )
cvFindFundamentalMat(&_imagePoints1, &_imagePoints2, &_F);
cvStereoRectifyUncalibrated(
&_imagePoints1, &_imagePoints2, &_F,
imageSize,
&_H1, &_H2, 3
);
cvInvert(&_M1, &_iM);
cvMatMul(&_H1, &_M1, &_R1);
cvMatMul(&_iM, &_R1, &_R1);
cvInvert(&_M2, &_iM);
cvMatMul(&_H2, &_M2, &_R2);
cvMatMul(&_iM, &_R2, &_R2);
//Precompute map for cvRemap()
cvInitUndistortRectifyMap(&_M1,&_D1,&_R1,&_M1,mx1,my1);
cvInitUndistortRectifyMap(&_M2,&_D1,&_R2,&_M2,mx2,my2);
}
else
assert(0);
cvReleaseMat( &mx1 );
cvReleaseMat( &my1 );
cvReleaseMat( &mx2 );
cvReleaseMat( &my2 );
cvReleaseMat( &img1r );
cvReleaseMat( &img2r );
cvReleaseMat( &disp );
}
}
int main(int argc, char** argv)
{
StereoCalib(argc > 1 ? argv[1] : "stereo_calib.txt", 0);
return 0;
}
Below are the extrinsic matrices obtained from the program.
R: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 9.9997887582765532e-001, 4.2746998112201760e-003,
-4.8964109286960510e-003, -4.1317666335754111e-003,
9.9957553950354616e-001, 2.8838677686057253e-002,
5.0176092857428471e-003, -2.8817837665560161e-002,
9.9957208635962669e-001 ]
T: !!opencv-matrix
rows: 3
cols: 1
dt: d
data: [ -8.3141294302865210e-001, -3.2181226087457654e-001,
-4.5924165239318537e-001 ]
R1: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 8.3000228682826938e-001, 3.1110786082949388e-001,
4.6293423160308594e-001, -3.1818678207964091e-001,
9.4578880995670123e-001, -6.5120647036789381e-002,
-4.5809756119155060e-001, -9.3249267508025396e-002,
8.8399728423766677e-001 ]
R2: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 8.2904793019998391e-001, 3.2089684317297251e-001,
4.5793530708249980e-001, -3.1381823995200708e-001,
9.4482404014772625e-001, -9.3944906367255512e-002,
-4.6281491084940990e-001, -6.5823621903907531e-002,
8.8400769741835628e-001 ]
P1: !!opencv-matrix
rows: 3
cols: 4
dt: d
data: [ -4.4953673002726404e+001, 0., -1.3375267505645752e+001, 0.,
0., -4.4953673002726404e+001, 2.4430860614776611e+002, 0., 0., 0.,
1., 0. ]
P2: !!opencv-matrix
rows: 3
cols: 4
dt: d
data: [ -4.4953673002726404e+001, 0., -1.3375267505645752e+001,
4.5081911684079330e+001, 0., -4.4953673002726404e+001,
2.4430860614776611e+002, 0., 0., 0., 1., 0. ]
And the intrinsic parameters found are as follows.
M1: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 4.3107336978610317e+002, 0., 3.4686501809547735e+002, 0.,
4.3107336978610317e+002, 1.9221944996848421e+002, 0., 0., 1. ]
D1: !!opencv-matrix
rows: 1
cols: 5
dt: d
data: [ -1.6825480517169825e-001, 1.0756945282000266e-001, 0., 0., 0. ]
M2: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 4.3107336978610317e+002, 0., 3.5310162800332756e+002, 0.,
4.3107336978610317e+002, 1.8963116073129768e+002, 0., 0., 1. ]
D2: !!opencv-matrix
rows: 1
cols: 5
dt: d
data: [ -1.9546177300030809e-001, 1.7624631189915094e-001, 0., 0., 0. ]
Any help would be much appreciated. I am not very experienced with OpenCV, and I have a hard time wrapping my head around what most of the functions are even doing. So I ca

Answer 1

I think I found the answer. After much experimenting, it seemed that the flag for cvStereoCalibrate, CV_CALIB_SAME_FOCAL_LENGTH, caused my output images to appear warped and/or not work. Also, I took many more chessboard pictures with a larger chessboard, and this seemed to help my results quite a bit.
Hope this helps anyone in the future.