我正在做 Bradski 的“Learning OpenCV”的示例 11-1。不幸的是，给定的示例在我的计算机上不起作用。
该程序应该使用棋盘校准相机，然后从相机输出不失真的视频输出。
校准部分工作正常，当程序试图不扭曲图像时会出现问题。我尝试了 cvUndistort2() 和 cvRemap()，在这两种情况下，输出窗口都会冻结并且程序崩溃，所以我必须强制关闭它。
这是代码：
#include <cv.h>
#include <highgui.h>
#include <stdio.h>
#include <stdlib.h>
#include <iostream>
int n_boards = 0;
int board_dt = 15;
int board_w;
int board_h;
int main(int argc, char* argv[]) {
CvCapture* capture;
/*
if(argc != 5){
printf("\nERROR: Wrong number of input parameters");
help();
return -1;
}
*/
board_w = 7;//atoi(argv[1]);
board_h = 7;//atoi(argv[2]);
n_boards = 8;//atoi(argv[3]);
CvSize board_sz = cvSize( board_w, board_h );
capture = cvCreateCameraCapture( 0 );
if(!capture) { printf("\nCouldn't open the camera\n"); return -1;}
cvNamedWindow( "Calibration" );
IplImage *image = cvQueryFrame( capture );
int board_n = board_w * board_h;
//ALLOCATE STORAGE
CvMat* image_points = cvCreateMat(n_boards*board_n,2,CV_32FC1);
CvMat* object_points = cvCreateMat(n_boards*board_n,3,CV_32FC1);
CvMat* point_counts = cvCreateMat(n_boards,1,CV_32SC1);
CvMat* intrinsic_matrix = cvCreateMat(3,3,CV_32FC1);
CvMat* distortion_coeffs = cvCreateMat(5,1,CV_32FC1);
CvPoint2D32f* corners = new CvPoint2D32f[ board_n ];
int corner_count;
int successes = 0;
int step, frame = 0;
IplImage *gray_image = cvCreateImage(cvGetSize(image),8,1);//subpixel
// CAPTURE CORNER VIEWS LOOP UNTIL WE'VE GOT n_boards
// SUCCESSFUL CAPTURES (ALL CORNERS ON THE BOARD ARE FOUND)
while (successes < n_boards) {
//Skip every board_dt frames to allow user to move chessboard
if((frame++ % board_dt) == 0) {
//Find chessboard corners:
int found = cvFindChessboardCorners(
image, board_sz, corners, &corner_count,
CV_CALIB_CB_ADAPTIVE_THRESH | CV_CALIB_CB_FILTER_QUADS
);
//Get Subpixel accuracy on those corners
cvCvtColor(image, gray_image, CV_BGR2GRAY);
cvFindCornerSubPix(gray_image, corners, corner_count,
cvSize(11,11),cvSize(-1,-1), cvTermCriteria(
CV_TERMCRIT_EPS+CV_TERMCRIT_ITER, 30, 0.1 ));
//Draw it
cvDrawChessboardCorners(image, board_sz, corners,
corner_count, found);
cvShowImage( "Calibration", image );
// If we got a good board, add it to our data
if( corner_count == board_n ) {
step = successes*board_n;
for( int i=step, j=0; j<board_n; ++i,++j ) {
CV_MAT_ELEM(*image_points, float,i,0) = corners[j].x;
CV_MAT_ELEM(*image_points, float,i,1) = corners[j].y;
CV_MAT_ELEM(*object_points,float,i,0) = j/board_w;
CV_MAT_ELEM(*object_points,float,i,1) = j%board_w;
CV_MAT_ELEM(*object_points,float,i,2) = 0.0f;
}
CV_MAT_ELEM(*point_counts, int,successes,0) = board_n;
successes++;
}
} //end skip board_dt between chessboard capture
//Handle pause/unpause and ESC
int c = cvWaitKey(15);
if (c == 'p'){
c = 0;
while(c != 'p' && c != 27){
c = cvWaitKey(250);
}
}
if(c == 27)
return 0;
image = cvQueryFrame( capture ); //Get next image
} //END COLLECTION WHILE LOOP.
//ALLOCATE MATRICES ACCORDING TO HOW MANY CHESSBOARDS FOUND
CvMat* object_points2 = cvCreateMat(successes*board_n,3,CV_32FC1);
CvMat* image_points2 = cvCreateMat(successes*board_n,2,CV_32FC1);
CvMat* point_counts2 = cvCreateMat(successes,1,CV_32SC1);
//TRANSFER THE POINTS INTO THE CORRECT SIZE MATRICES
for(int i = 0; i<successes*board_n; ++i) {
CV_MAT_ELEM( *image_points2, float, i, 0) = CV_MAT_ELEM( *image_points, float, i, 0);
CV_MAT_ELEM( *image_points2, float, i, 1) = CV_MAT_ELEM( *image_points, float, i, 1);
CV_MAT_ELEM( *object_points2, float, i, 0) = CV_MAT_ELEM( *object_points, float, i, 0) ;
CV_MAT_ELEM( *object_points2, float, i, 1) = CV_MAT_ELEM( *object_points, float, i, 1) ;
CV_MAT_ELEM( *object_points2, float, i, 2) = CV_MAT_ELEM( *object_points, float, i, 2) ;
}
for(int i=0; i<successes; ++i){ //These are all the same number
CV_MAT_ELEM( *point_counts2, int, i, 0) = CV_MAT_ELEM( *point_counts, int, i, 0);
}
// Initialize the intrinsic matrix such that the two focal
// lengths have a ratio of 1.0
CV_MAT_ELEM( *intrinsic_matrix, float, 0, 0 ) = 1.0f;
CV_MAT_ELEM( *intrinsic_matrix, float, 1, 1 ) = 1.0f;
//CALIBRATE THE CAMERA!
cvCalibrateCamera2(
object_points2, image_points2,
point_counts2, cvGetSize( image ),
intrinsic_matrix, distortion_coeffs,
NULL, NULL,0 //CV_CALIB_FIX_ASPECT_RATIO
);
// SAVE THE INTRINSICS AND DISTORTIONS
cvSave("Intrinsics.xml",intrinsic_matrix);
cvSave("Distortion.xml",distortion_coeffs);
cvReleaseMat(&object_points);
cvReleaseMat(&image_points);
cvReleaseMat(&point_counts);
cvReleaseMat(&object_points2);
cvReleaseMat(&image_points2);
cvReleaseMat(&point_counts2);
cvReleaseMat(&intrinsic_matrix);
cvReleaseMat(&distortion_coeffs);
// EXAMPLE OF LOADING THESE MATRICES BACK IN:
CvMat *intrinsic = (CvMat*)cvLoad("Intrinsics.xml");
CvMat *distortion= (CvMat*)cvLoad("Distortion.xml");
// Build the undistort map that we will use for all
// subsequent frames.
IplImage* mapx = cvCreateImage( cvGetSize(image), IPL_DEPTH_32F, 1 );
IplImage* mapy = cvCreateImage( cvGetSize(image), IPL_DEPTH_32F, 1 );
cvInitUndistortMap(
intrinsic,
distortion,
mapx,
mapy
);
// Just run the camera to the screen, now showing the raw and
// the undistorted image
cvNamedWindow( "Undistort" );
while(image) {
IplImage *t = cvCloneImage(image);
// PROBLEM HERE!
//cvRemap( image, t, mapx, mapy ); // Undistort image
cvUndistort2(image, t, intrinsic, distortion);
cvShowImage( "Calibration", image ); // Show raw image
cvShowImage( "Undistort", t); // Show corrected image
cvReleaseImage(&t);
//Handle pause/unpause and ESC
int c = cvWaitKey(30);
if(c == 'p') {
c = 0;
while(c != 'p' && c != 27) {
c = cvWaitKey(250);
}
}
if(c == 27)
break;
image = cvQueryFrame( capture );
}
cvReleaseMat(&intrinsic);
cvReleaseMat(&distortion);
cvReleaseImage(&image);
cvReleaseImage(&gray_image);
cvReleaseImage(&mapx);
cvReleaseImage(&mapy);
cvDestroyWindow("Calibration");
cvDestroyWindow("Undistort");
return 0;
}
以下是保存在 Intrinsics.xml 和 Distortion.xml 中的校准结果：
Intrinsics.xml：
<?xml version="1.0"?>
<opencv_storage>
<Intrinsics type_id="opencv-matrix">
<rows>3</rows>
<cols>3</cols>
<dt>f</dt>
<data>
649.64843750 0. 288.47882080 0. 647.89129639 271.92953491 0. 0. 1.</data></Intrinsics>
</opencv_storage>
失真.xml：
<?xml version="1.0"?>
<opencv_storage>
<Distortion type_id="opencv-matrix">
<rows>5</rows>
<cols>1</cols>
<dt>f</dt>
<data>
-0.37764871 22.05950546 0.06449836 -0.03288389 -209.10910034</data></Distortion>
</opencv_storage>
我使用 OpenCV2.0、Eclipse、Windows Vista。相机是笔记本电脑的网络摄像头。