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aruco: use densely packed array for pose computation

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allows using Mat and vector<Vec3d> as argument for rvecs, tvecs that are
allocated at once.
This commit is contained in:
Pavel Rojtberg
2015-10-08 18:42:05 +02:00
parent b36d51185f
commit ee61cba9f9
11 changed files with 23 additions and 26 deletions
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4
modules/aruco/include/opencv2/aruco.hpp
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@@ -190,9 +190,9 @@ CV_EXPORTS void detectMarkers(InputArray image, Dictionary dictionary, OutputArr
* \f$A = \vecthreethree{f_x}{0}{c_x}{0}{f_y}{c_y}{0}{0}{1}\f$
* @param distCoeffs vector of distortion coefficients
* \f$(k_1, k_2, p_1, p_2[, k_3[, k_4, k_5, k_6],[s_1, s_2, s_3, s_4]])\f$ of 4, 5, 8 or 12 elements
* @param rvecs array of output rotation vectors (@sa Rodrigues) (e.g. std::vector<cv::Mat>>).
* @param rvecs array of output rotation vectors (@sa Rodrigues) (e.g. std::vector<cv::Vec3d>>).
* Each element in rvecs corresponds to the specific marker in imgPoints.
* @param tvecs array of output translation vectors (e.g. std::vector<cv::Mat>>).
* @param tvecs array of output translation vectors (e.g. std::vector<cv::Vec3d>>).
* Each element in tvecs corresponds to the specific marker in imgPoints.
*
* This function receives the detected markers and returns their pose estimation respect to

2
modules/aruco/samples/detect_board.cpp
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@@ -207,7 +207,7 @@ int main(int argc, char *argv[]) {
vector< int > ids;
vector< vector< Point2f > > corners, rejected;
Mat rvec, tvec;
Vec3d rvec, tvec;
// detect markers
aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);

2
modules/aruco/samples/detect_board_charuco.cpp
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@@ -204,7 +204,7 @@ int main(int argc, char *argv[]) {
vector< int > markerIds, charucoIds;
vector< vector< Point2f > > markerCorners, rejectedMarkers;
vector< Point2f > charucoCorners;
Mat rvec, tvec;
Vec3d rvec, tvec;
// detect markers
aruco::detectMarkers(image, dictionary, markerCorners, markerIds, detectorParams,

2
modules/aruco/samples/detect_diamonds.cpp
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@@ -202,7 +202,7 @@ int main(int argc, char *argv[]) {
vector< int > markerIds;
vector< Vec4i > diamondIds;
vector< vector< Point2f > > markerCorners, rejectedMarkers, diamondCorners;
vector< Mat > rvecs, tvecs;
vector< Vec3d > rvecs, tvecs;
// detect markers
aruco::detectMarkers(image, dictionary, markerCorners, markerIds, detectorParams,

2
modules/aruco/samples/detect_markers.cpp
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@@ -194,7 +194,7 @@ int main(int argc, char *argv[]) {
vector< int > ids;
vector< vector< Point2f > > corners, rejected;
vector< Mat > rvecs, tvecs;
vector< Vec3d > rvecs, tvecs;
// detect markers and estimate pose
aruco::detectMarkers(image, dictionary, corners, ids, detectorParams, rejected);

25
modules/aruco/src/aruco.cpp
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@@ -821,9 +821,9 @@ void detectMarkers(InputArray _image, Dictionary dictionary, OutputArrayOfArrays
*/
class SinglePoseEstimationParallel : public ParallelLoopBody {
public:
SinglePoseEstimationParallel(Mat *_markerObjPoints, InputArrayOfArrays _corners,
SinglePoseEstimationParallel(Mat& _markerObjPoints, InputArrayOfArrays _corners,
InputArray _cameraMatrix, InputArray _distCoeffs,
OutputArrayOfArrays _rvecs, OutputArrayOfArrays _tvecs)
Mat& _rvecs, Mat& _tvecs)
: markerObjPoints(_markerObjPoints), corners(_corners), cameraMatrix(_cameraMatrix),
distCoeffs(_distCoeffs), rvecs(_rvecs), tvecs(_tvecs) {}
@@ -832,18 +832,18 @@ class SinglePoseEstimationParallel : public ParallelLoopBody {
const int end = range.end;
for(int i = begin; i < end; i++) {
solvePnP(*markerObjPoints, corners.getMat(i), cameraMatrix, distCoeffs, rvecs.getMat(i),
tvecs.getMat(i));
solvePnP(markerObjPoints, corners.getMat(i), cameraMatrix, distCoeffs,
rvecs.at<Vec3d>(0, i), tvecs.at<Vec3d>(0, i));
}
}
private:
SinglePoseEstimationParallel &operator=(const SinglePoseEstimationParallel &); // to quiet MSVC
Mat *markerObjPoints;
Mat& markerObjPoints;
InputArrayOfArrays corners;
InputArray cameraMatrix, distCoeffs;
OutputArrayOfArrays rvecs, tvecs;
Mat& rvecs, tvecs;
};
@@ -860,13 +860,10 @@ void estimatePoseSingleMarkers(InputArrayOfArrays _corners, float markerLength,
Mat markerObjPoints;
_getSingleMarkerObjectPoints(markerLength, markerObjPoints);
int nMarkers = (int)_corners.total();
_rvecs.create(nMarkers, 1, CV_32FC1);
_tvecs.create(nMarkers, 1, CV_32FC1);
_rvecs.create(nMarkers, 1, CV_64FC3);
_tvecs.create(nMarkers, 1, CV_64FC3);
for(int i = 0; i < nMarkers; i++) {
_rvecs.create(3, 1, CV_64FC1, i, true);
_tvecs.create(3, 1, CV_64FC1, i, true);
}
Mat rvecs = _rvecs.getMat(), tvecs = _tvecs.getMat();
//// for each marker, calculate its pose
// for (int i = 0; i < nMarkers; i++) {
@@ -876,8 +873,8 @@ void estimatePoseSingleMarkers(InputArrayOfArrays _corners, float markerLength,
// this is the parallel call for the previous commented loop (result is equivalent)
parallel_for_(Range(0, nMarkers),
SinglePoseEstimationParallel(&markerObjPoints, _corners, _cameraMatrix,
_distCoeffs, _rvecs, _tvecs));
SinglePoseEstimationParallel(markerObjPoints, _corners, _cameraMatrix,
_distCoeffs, rvecs, tvecs));
}

2
modules/aruco/test/test_charucodetection.cpp
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@@ -515,7 +515,7 @@ void CV_CharucoDiamondDetection::run(int) {
}
// estimate diamond pose
vector< Mat > estimatedRvec, estimatedTvec;
vector< Vec3d > estimatedRvec, estimatedTvec;
aruco::estimatePoseSingleMarkers(diamondCorners, squareLength, cameraMatrix,
distCoeffs, estimatedRvec, estimatedTvec);

4
modules/aruco/tutorials/aruco_board_detection/aruco_board_detection.markdown
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@@ -64,7 +64,7 @@ The aruco module provides a specific function, ```estimatePoseBoard()```, to per
cv::aruco::detectMarkers(inputImage, board.dictionary, markerCorners, markerIds);
// if at least one marker detected
if(markerIds.size() > 0) {
cv::Mat rvec, tvec;
cv::Vec3d rvec, tvec;
int valid = cv::aruco::estimatePoseBoard(markerCorners, markerIds, board, cameraMatrix, distCoeffs, rvec, tvec);
}
```
@@ -181,7 +181,7 @@ Finally, a full example of board detection:
if (ids.size() > 0) {
cv::aruco::drawDetectedMarkers(imageCopy, corners, ids);
cv::Mat rvec, tvec;
cv::Vec3d rvec, tvec;
int valid = estimatePoseBoard(corners, ids, board, cameraMatrix, distCoeffs, rvec, tvec);
// if at least one board marker detected

2
modules/aruco/tutorials/aruco_detection/aruco_detection.markdown
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@@ -256,7 +256,7 @@ The aruco module provides a function to estimate the poses of all the detected m
``` c++
Mat cameraMatrix, distCoeffs;
...
vector< Mat > rvecs, tvecs;
vector< Vec3d > rvecs, tvecs;
cv::aruco::estimatePoseSingleMarkers(corners, 0.05, cameraMatrix, distCoeffs, rvecs, tvecs);
```

2
modules/aruco/tutorials/charuco_detection/charuco_detection.markdown
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@@ -294,7 +294,7 @@ A full example of ChArUco detection with pose estimation:
// if at least one charuco corner detected
if(charucoIds.size() > 0) {
cv::aruco::drawDetectedCornersCharuco(imageCopy, charucoCorners, charucoIds, cv::Scalar(255, 0, 0));
cv::Mat rvec, tvec;
cv::Vec3d rvec, tvec;
bool valid = cv::aruco::estimatePoseCharucoBoard(charucoCorners, charucoIds, board, cameraMatrix, distCoeffs, rvec, tvec);
// if charuco pose is valid
if(valid)

2
modules/aruco/tutorials/charuco_diamond_detection/charuco_diamond_detection.markdown
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@@ -133,7 +133,7 @@ i.e. using the ```estimatePoseSingleMarkers()``` function. For instance:
cv::aruco::detectCharucoDiamond(inputImage, markerCorners, markerIds, squareLength / markerLength, diamondCorners, diamondIds);
// estimate poses
std::vector<cv::Mat> rvecs, tvecs;
std::vector<cv::Vec3d> rvecs, tvecs;
cv::aruco::estimatePoseSingleMarkers(diamondCorners, squareLength, camMatrix, distCoeffs, rvecs, tvecs);
// draw axis