我正在尝试使用OpenCV中包含的Aruco库进行基本姿态估计。
下的示例http://docs.opencv.org/trunk/d5/dae/tutorial_aruco_detection.html有什么问题
单个标记的姿势估计的基本完整示例：
代码如下（由示例代码和我的一些代码组成，用于读出相机的参数和失真系数）：
// http://docs.opencv.org/3.1.0/d5/dae/tutorial_aruco_detection.html
//
#include "stdafx.h"
#include <vector>
#include "opencv2\Core\types.hpp"
#include "opencv2\core.hpp"
#include "opencv2/opencv.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/videoio.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/opencv.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/tracking.hpp"
#include <opencv2/aruco.hpp>
#include <opencv2/aruco/charuco.hpp>
int _tmain(int argc, _TCHAR* argv[]) {
printf("OpenCV: %s", cv::getBuildInformation().c_str());
cv::VideoCapture inputVideo;
inputVideo.open(0);
cv::Mat cameraMatrix, distCoeffs;
// camera parameters are read from somewhere
////readCameraParameters(cameraMatrix, distCoeffs);
cv::String filename = "C:\\C\\buildVs\\opencv-master\\samples\\cpp\\tutorial_code\\calib3d\\camera_calibration\\myCalibratedForBuiltinCamera.yml";
float markerLength = 0.05f; // length in meters (?) of a marker
// read calibration file
//cout << endl << "Reading: " << endl;
cv::FileStorage fs;
fs.open(filename, cv::FileStorage::READ);
// cv::Mat cameraMatrix, distCoeffs;
fs["Camera_Matrix"] >> cameraMatrix;
fs["Distortion_Coefficients"] >> distCoeffs;
cv::Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
while (inputVideo.grab()) {
cv::Mat image, imageCopy;
inputVideo.retrieve(image);
image.copyTo(imageCopy);
std::vector<int> ids;
std::vector<std::vector<cv::Point2f> > corners;
cv::aruco::detectMarkers(image, dictionary, corners, ids);
// if at least one marker detected
if (ids.size() > 0) {
cv::aruco::drawDetectedMarkers(imageCopy, corners, ids);
std::vector< cv::Mat > rvecs, tvecs;
cv::aruco::estimatePoseSingleMarkers(corners, 0.05, cameraMatrix, distCoeffs, rvecs, tvecs);
// draw axis for each marker
for (int i = 0; i<ids.size(); i++)
cv::aruco::drawAxis(imageCopy, cameraMatrix, distCoeffs, rvecs[i], tvecs[i], 0.1);
}
cv::imshow("out", imageCopy);
char key = (char)cv::waitKey(2);
if (key == 27)
break;
}
return 0;
}
当我将其复制到一个新项目并尝试将其与一些aruco :: DICT_6X6_250标记一起使用时，它会崩溃。
其中一个原因可能是系数格式错误，我使用的校准文件包含以下内容：
%YAML:1.0
calibration_Time: "08/19/11 20:44:38"
nrOfFrames: 8
image_Width: 640
image_Height: 480
board_Width: 9
board_Height: 6
square_Size: 50.
FixAspectRatio: 1.
# flags: +fix_aspectRatio +fix_principal_point +zero_tangent_dist
flagValue: 14
Camera_Matrix: !!opencv-matrix
rows: 3
cols: 3
dt: d
data: [ 6.5746697810243404e+002, 0., 3.1950000000000000e+002, 0.,
6.5746697810243404e+002, 2.3950000000000000e+002, 0., 0., 1. ]
Distortion_Coefficients: !!opencv-matrix
rows: 5
cols: 1
dt: d
data: [ -4.1802327018241026e-001, 5.0715243805833121e-001, 0., 0.,
-5.7843596847939704e-001 ]
Avg_Reprojection_Error: 3.8441346462381665e-001
Per_View_Reprojection_Errors: !!opencv-matrix
rows: 8
cols: 1
dt: f
data: [ 5.04357755e-001, 4.85754758e-001, 3.99563968e-001,
4.13829178e-001, 3.53570908e-001, 3.21116358e-001,
2.74473161e-001, 2.39761785e-001 ]
# a set of 6-tuples (rotation vector + translation vector) for each view
Extrinsic_Parameters: !!opencv-matrix
rows: 8
cols: 6
dt: d
data: [ -7.8704123655486097e-002, -1.5922384772614945e-001,
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-1.5876137659782963e+000, -1.0242234847115104e+002,
2.2583088401423066e+002, 1.1125972190244058e+003 ]
Image_points: !!opencv-matrix
rows: 8
cols: 54
dt: "2f"
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2.26512482e+002, 2.49628265e+002, 2.25067520e+002,
2.85066406e+002, 2.23593185e+002, 3.20846680e+002,
2.22337708e+002, 3.56862885e+002, 2.21191040e+002,
3.93279907e+002, 2.19905640e+002, 4.29202271e+002,
2.18870361e+002, 4.64728424e+002, 2.17972977e+002,
1.83496948e+002, 2.62963226e+002, 2.16930527e+002,
2.61755219e+002, 2.51115829e+002, 2.60777222e+002,
2.86553406e+002, 2.59500336e+002, 3.22299896e+002,
2.58380737e+002, 3.58307648e+002, 2.57236694e+002,
3.94551819e+002, 2.56009125e+002, 4.30358948e+002,
2.54925797e+002, 4.65684998e+002, 2.54021484e+002,
1.85461685e+002, 2.97687378e+002, 2.18712234e+002,
2.96999207e+002, 2.52770218e+002, 2.96270752e+002,
2.88213776e+002, 2.95168213e+002, 3.23698334e+002,
2.94233032e+002, 3.59477722e+002, 2.93170715e+002,
3.95647766e+002, 2.91897400e+002, 4.31309845e+002,
2.90856995e+002, 4.66494110e+002, 2.89726410e+002,
1.87661331e+002, 3.32186188e+002, 2.20767746e+002,
3.31906250e+002, 2.54839096e+002, 3.31398651e+002,
2.89963745e+002, 3.30524139e+002, 3.25207642e+002,
3.29771820e+002, 3.60686035e+002, 3.28762695e+002,
3.96576447e+002, 3.27542206e+002, 4.31994415e+002,
3.26294189e+002, 4.66894653e+002, 3.24949921e+002,
2.03543015e+002, 1.77473557e+002, 2.32777847e+002,
1.74712509e+002, 2.62628723e+002, 1.72331970e+002,
2.93045898e+002, 1.69686768e+002, 3.23527618e+002,
1.67496246e+002, 3.54206787e+002, 1.65446075e+002,
3.85180176e+002, 1.63360580e+002, 4.15484253e+002,
1.61536423e+002, 4.45720947e+002, 1.59896164e+002,
2.05864395e+002, 2.07228104e+002, 2.35242096e+002,
2.04699326e+002, 2.64853973e+002, 2.02407455e+002,
2.95353882e+002, 1.99972321e+002, 3.25811890e+002,
1.97671921e+002, 3.56471252e+002, 1.95763168e+002,
3.87280548e+002, 1.93597977e+002, 4.17615814e+002,
1.91867371e+002, 4.48018677e+002, 1.90067413e+002,
2.08421249e+002, 2.37166977e+002, 2.37513824e+002,
2.34982773e+002, 2.67261261e+002, 2.32802841e+002,
2.97555817e+002, 2.30466080e+002, 3.28118103e+002,
2.28462463e+002, 3.58699707e+002, 2.26417038e+002,
3.89468842e+002, 2.24356827e+002, 4.19895996e+002,
2.22421921e+002, 4.50077850e+002, 2.20683517e+002,
2.11095444e+002, 2.66940186e+002, 2.40241348e+002,
2.64970093e+002, 2.69563019e+002, 2.63153290e+002,
2.99863464e+002, 2.60983551e+002, 3.30282440e+002,
2.58911560e+002, 3.60724792e+002, 2.56935730e+002,
3.91487915e+002, 2.54799423e+002, 4.21789093e+002,
2.52929688e+002, 4.51818481e+002, 2.51059357e+002,
2.13829117e+002, 2.96591217e+002, 2.42742859e+002,
2.94884583e+002, 2.72209076e+002, 2.93215668e+002,
3.02402985e+002, 2.91230591e+002, 3.32536072e+002,
2.89165192e+002, 3.62860901e+002, 2.87413605e+002,
3.93481842e+002, 2.85199615e+002, 4.23728851e+002,
2.83277496e+002, 4.53453094e+002, 2.81229309e+002,
2.16799316e+002, 3.25975220e+002, 2.45605515e+002,
3.24619904e+002, 2.74777344e+002, 3.22958679e+002,
3.04762817e+002, 3.21008057e+002, 3.34797150e+002,
3.19291443e+002, 3.65005798e+002, 3.17295044e+002,
3.95311981e+002, 3.15296021e+002, 4.25312592e+002,
3.13086945e+002, 4.54931152e+002, 3.11027130e+002,
2.60550232e+002, 3.70739563e+002, 2.59674011e+002,
3.42115936e+002, 2.58910492e+002, 3.13278015e+002,
2.58195618e+002, 2.84013580e+002, 2.57727173e+002,
2.55017166e+002, 2.57326263e+002, 2.25760986e+002,
2.57096619e+002, 1.96577972e+002, 2.57031860e+002,
1.68026199e+002, 2.56873383e+002, 1.39550308e+002,
2.89019318e+002, 3.70481354e+002, 2.88355560e+002,
3.41833252e+002, 2.87601471e+002, 3.12872925e+002,
2.87057190e+002, 2.83485535e+002, 2.86599762e+002,
2.54255096e+002, 2.86174438e+002, 2.25023285e+002,
2.85775940e+002, 1.95715347e+002, 2.85577087e+002,
1.66989502e+002, 2.85395477e+002, 1.38597382e+002,
3.18072754e+002, 3.70118317e+002, 3.17432709e+002,
3.41398743e+002, 3.16917267e+002, 3.12476044e+002,
3.16284363e+002, 2.83001587e+002, 3.15799072e+002,
2.53725845e+002, 3.15411957e+002, 2.24337708e+002,
3.15070374e+002, 1.95034119e+002, 3.14736847e+002,
1.66195313e+002, 3.14439789e+002, 1.37797058e+002,
3.47083588e+002, 3.69678101e+002, 3.46717987e+002,
3.40949524e+002, 3.46185303e+002, 3.12009857e+002,
3.45728088e+002, 2.82454071e+002, 3.45226624e+002,
2.53109863e+002, 3.44883606e+002, 2.23839539e+002,
3.44373535e+002, 1.94399933e+002, 3.43879852e+002,
1.65690643e+002, 3.43438629e+002, 1.37252930e+002,
3.76341522e+002, 3.68972321e+002, 3.76086884e+002,
3.40412842e+002, 3.75708893e+002, 3.11398376e+002,
3.75143494e+002, 2.81901520e+002, 3.74762970e+002,
2.52577988e+002, 3.74223969e+002, 2.23348221e+002,
3.73600891e+002, 1.93979538e+002, 3.72983917e+002,
1.65201294e+002, 3.72517273e+002, 1.36871033e+002,
4.05512115e+002, 3.68243225e+002, 4.05366333e+002,
3.39678650e+002, 4.05090027e+002, 3.10679108e+002,
4.04612366e+002, 2.81203522e+002, 4.04152649e+002,
2.52051605e+002, 4.03539703e+002, 2.22930420e+002,
4.02903351e+002, 1.93625381e+002, 4.02272827e+002,
1.65004440e+002, 4.01353333e+002, 1.36796814e+002 ]
我使用visual studio 2013在Windows下运行它，OpenCV版本是3.1.0-dev