对不同摄像机(RGB和红外)进行校准 [英] stereoCalibrate for different cameras (rgb and infrared)
问题描述
我在校准两个摄像机时遇到问题:第一个是rgb，第二个是红外.它们具有不同的分辨率(我调整了大小并裁剪了较大的图像)，焦距等...
I have problems with calibrating two cameras: first is rgb and second is infrared. They have different resolution (I resized and croped bigger image), focal length, etc...
示例:
RGB 1920x1080
RGB 1920x1080
红外512x424
Infrared 512x424
如何相互校准?我应该在stereoCalibrate中使用哪些参数. 默认样本stereo_calib.cpp会产生很大的错误. 像这样的东西:
How to calibrate them to each other? What parameters should I use in stereoCalibrate. Default sample stereo_calib.cpp produce very big error. Something like this: https://www.dropbox.com/s/x57rrzp1ejm3cac/%D0%A1%D0%BA%D1%80%D0%B8%D0%BD%D1%88%D0%BE%D1%82%202014-04-05%2012.54.17.png
完成，RMS错误= 4.1026
done with RMS error=4.1026
平均投影错误err = 10.2601
average reprojection err = 10.2601
更新
我使用Calibration.cpp示例分别为每个摄像机生成了校准参数.对于RGB相机，我首先调整大小并裁剪图像以使其分辨率与IR相机(512x424)相匹配，然后进行校准.对于RGB摄像机，我得到camera.yml，对于红外摄像机，我得到camera_ir.yml. 然后，我尝试使用修改后的stereo_calib.cpp示例进行立体声校准.在调用stereoticCalibrate之前，我从文件中读取了相机的camera_matrix和畸变系数参数，并将这些矩阵放入stereoCalibrate中.
I generated calibration parameters for each cameras independently using calibration.cpp example. For RGB camera I first resize and crop image to resolution matches IR camera (512x424), then calibrate. For RGB camera I get camera.yml, for IR camera I get camera_ir.yml. Then I try make stereo calibration using modified stereo_calib.cpp example. Before call stereoCalibrate I read camera_matrix and distortion_coefficients params for cameras from files, and put these matrices into stereoCalibrate.
FileStorage rgbCamSettings("camera.yml", CV_STORAGE_READ);
Mat rgbCameraMatrix;
Mat rgbDistCoeffs;
rgbCamSettings["camera_matrix"] >> rgbCameraMatrix;
rgbCamSettings["distortion_coefficients"] >> rgbDistCoeffs;
FileStorage irCamSettings("camera_ir.yml", CV_STORAGE_READ);
Mat irCameraMatrix;
Mat irDistCoeffs;
irCamSettings["camera_matrix"] >> irCameraMatrix;
irCamSettings["distortion_coefficients"] >> irDistCoeffs;
Mat cameraMatrix[2], distCoeffs[2];
cameraMatrix[0] = rgbCameraMatrix;
cameraMatrix[1] = irCameraMatrix;
distCoeffs[0] = rgbDistCoeffs;
distCoeffs[1] = irDistCoeffs;
Mat R, T, E, F;
double rms = stereoCalibrate(objectPoints, imagePoints[0], imagePoints[1],
cameraMatrix[0], distCoeffs[0],
cameraMatrix[1], distCoeffs[1],
imageSize, R, T, E, F,
TermCriteria(CV_TERMCRIT_ITER+CV_TERMCRIT_EPS, 50, 1e-6),
CV_CALIB_FIX_INTRINSIC +
CV_CALIB_USE_INTRINSIC_GUESS
);
推荐答案
在Dropbox上看不到图像(为什么不将图像放在堆栈交换中?)，但似乎束调整未收敛.您应该尝试以下操作:
Can't see your images on Dropbox (why not put your images on stack exchange?), but it seems like the bundle adjustment does not converge. You should try the following:
-
使用
cv::calibrateCamera(链接)，然后获取每个摄像机的摄像机矩阵K和失真系数D.
Calibrate each camera independently using
cv::calibrateCamera(link) and get the camera matrix K and distortion coefficients D for each camera.
使用cv::stereoCalibrate(链接)，其中包含估算的K和D并启用了标志CV_CALIB_USE_INTRINSIC_GUESS和CV_CALIB_FIX_INTRINSIC.
Estimate the rotation R and the translation T between the two cameras using cv::stereoCalibrate (link) with the estimated K and D and with flags CV_CALIB_USE_INTRINSIC_GUESS and CV_CALIB_FIX_INTRINSIC enabled.
这样做将使摄像机矩阵的估计和失真系数与旋转和平移的估计脱钩，这将大大改善残余误差.
Doing so will decouple the estimation of both camera matrices and distortion coefficients from the estimation of the rotation and translation, which should improve the residual error a lot.
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