我正在使用OpenCV Viz和ARUCO开发一个简单的基于标记的增强现实应用程序。我只想在标记上可视化一个 3D 对象(以 PLY 格式)。
我可以毫无问题地使用 ARUCO 运行标记检测和姿态估计(返回旋转和平移向量)。我可以在 Viz 窗口中可视化任何 3D 对象(PLY 格式)和相机帧。但是,我坚持使用 ARUCO 的旋转和平移矢量输出来定位标记上的 3D 模型。
我正在使用旋转和平移向量创建仿射变换并将其应用于 3D 模型。这是对的吗?我应该如何使用平移和旋转向量?
下面是我的代码片段。
// Camera calibration outputs
cv::Mat cameraMatrix, distCoeffs;
loadIntrinsicCameraParameters(cameraMatrix, distCoeffs);
// Marker dictionary
Ptr<cv::aruco::Dictionary> dictionary = cv::aruco::getPredefinedDictionary(cv::aruco::DICT_6X6_250);
viz::Viz3d myWindow("Coordinate Frame");
cv::Mat image;
// Webcam frame pose, without this frame is upside-down
Affine3f imagePose(Vec3f(3.14159,0,0), Vec3f(0,0,0));
// Viz viewer pose to see whole webcam frame
Vec3f cam_pos( 0.0f,0.0f,900.0f), cam_focal_point(0.0f,0.0f,0.0f), cam_y_dir(0.0f,0.0f,0.0f);
Affine3f viewerPose = viz::makeCameraPose(cam_pos, cam_focal_point, cam_y_dir);
// Video capture from source
VideoCapture cap(camID);
int frame_width = cap.get(CV_CAP_PROP_FRAME_WIDTH);
int frame_height = cap.get(CV_CAP_PROP_FRAME_HEIGHT);
cap >> image;
// Load mash data
viz::WMesh batman(viz::Mesh::load("../data/bat.ply"));
viz::WImage3D img(image, Size2d(frame_width, frame_height));
// Show camera frame, mesh and a coordinate widget (for debugging)
myWindow.showWidget("Image", img);
myWindow.showWidget("Batman", batman);
myWindow.showWidget("Coordinate Widget", viz::WCoordinateSystem(5.0));
myWindow.setFullScreen(true);
myWindow.setViewerPose(viewerPose);
// Rotation vector of 3D model
Mat rot_vec = Mat::zeros(1,3,CV_32F);
cv::Vec3d rvec, tvec;
// ARUCO outputs
float roll, pitch, yaw;
float x, y, z;
while (!myWindow.wasStopped()) {
if (cap.read(image)) {
cv::Mat image, imageCopy;
cap.retrieve(image);
image.copyTo(imageCopy);
// Marker detection
std::vector<int> ids;
std::vector<std::vector<cv::Point2f> > corners;
cv::aruco::detectMarkers(image, dictionary, corners, ids);
if (ids.size() > 0){
// Draw a green line around markers
cv::aruco::drawDetectedMarkers(imageCopy, corners, ids);
vector<Vec3d> rvecs, tvecs;
// Get rotation and translation vectors of each markers
cv::aruco::estimatePoseSingleMarkers(corners, 0.05, cameraMatrix, distCoeffs, rvecs, tvecs);
for(int i=0; i<ids.size(); i++){
cv::aruco::drawAxis(imageCopy, cameraMatrix, distCoeffs, rvecs[i], tvecs[i], 0.1);
// Take only the first marker's rotation and translation to visualize 3D model on this marker
rvec = rvecs[0];
tvec = tvecs[0];
roll = rvec[0];
pitch = rvec[1];
yaw = rvec[2];
x = tvec[0];
y = tvec[1];
z = tvec[2];
qDebug() << rvec[0] << "," << rvec[1] << "," << rvec[2] << "---" << tvec[0] << "," << tvec[1] << "," << tvec[2];
}
}
// Show camera frame in Viz window
img.setImage(imageCopy);
img.setPose(imagePose);
}
// Create affine pose from rotation and translation vectors
rot_vec.at<float>(0,0) = roll;
rot_vec.at<float>(0,1) = pitch;
rot_vec.at<float>(0,2) = yaw;
Mat rot_mat;
Rodrigues(rot_vec, rot_mat);
Affine3f pose(rot_mat, Vec3f(x, y, z));
// Set the pose of 3D model
batman.setPose(pose);
myWindow.spinOnce(1, true);
}