Ask Your Question

Revision history [back]

click to hide/show revision 1
initial version

Online estimation of euler angels (camera pose) using images from camera and opencv library

I'm working on a android application and I need to estimate online camera rotation in 3D-plan using images from camera and opencv library. I like to calculate Euler angles.

I have read this and this page and I can estimate homography matrix like here.

My first question is, should I really know the camera intrinsic matrix from camera calibrtion or is the homography matrix (camera extrinsic) enough to estimate euler angles (pitch, roll, yaw)?

If homography matrix is enough, how can I do it exactly?

Sorry, I am really beginner with opencv and cannot decompose "Mat" of homography to rotation matrix and translation matrix like describes here. How can I implement euler angles in android?

Thank you very much for any response!

Online estimation of euler angels (camera pose) using images from camera and opencv library

I'm working on a android application and I need to estimate online camera rotation in 3D-plan using images from camera and opencv library. I like to calculate Euler angles.

I have read this and this page and I can estimate homography matrix like here.

My first question is, should I really know the camera intrinsic matrix from camera calibrtion or is the homography matrix (camera extrinsic) enough to estimate euler angles (pitch, roll, yaw)?

If homography matrix is enough, how can I do it exactly?

Sorry, I am really beginner with opencv and cannot decompose "Mat" of homography to rotation matrix and translation matrix like describes here. How can I implement euler angles in android?

This is my code, but i it return a null-vector for double[] eulerArray!!! Can somebody help me?! Thank you very much for any response!

 public void findEulerAngles(MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfDMatch matches){

    KeyPoint[] k1 = keypoints1.toArray();
    KeyPoint[] k2 = keypoints2.toArray();

    List<DMatch> matchesList = matches.toList();
    List<KeyPoint> referenceKeypointsList = keypoints2.toList();
    List<KeyPoint> sceneKeypointsList = keypoints1.toList();
    // Calculate the max and min distances between keypoints.
    double maxDist = 0.0;
    double minDist = Double.MAX_VALUE;
    for(DMatch match : matchesList) {
        double dist = match.distance;
        if (dist < minDist) {
            minDist = dist;
        }
        if (dist > maxDist) {
            maxDist = dist;
        }
    }

    // Identify "good" keypoints based on match distance.
    List<Point3> goodReferencePointsList = new ArrayList<Point3>();
    ArrayList<Point> goodScenePointsList = new ArrayList<Point>();
    double maxGoodMatchDist = 1.75 * minDist;
    for(DMatch match : matchesList) {
        if (match.distance < maxGoodMatchDist) {
            Point kk2 = k2[match.queryIdx].pt;
            Point kk1 = k1[match.trainIdx].pt;

            Point3 point3 = new Point3(kk1.x, kk1.y, 0.0);
            goodReferencePointsList.add(point3);
            goodScenePointsList.add( kk2);
        }
    }


    if (goodReferencePointsList.size() < 4 || goodScenePointsList.size() < 4) {
        // There are too few good points to find the pose.
        return;
    }

    MatOfPoint3f goodReferencePoints = new MatOfPoint3f();
    goodReferencePoints.fromList(goodReferencePointsList);
    MatOfPoint2f goodScenePoints = new MatOfPoint2f();
    goodScenePoints.fromList(goodScenePointsList);

    MatOfDouble mRMat = new MatOfDouble(3, 3, CvType.CV_32F);
    MatOfDouble mTVec = new MatOfDouble(3, 1, CvType.CV_32F);

    //TODO: solve camera intrinsic matrix
    Mat intrinsics = Mat.eye(3, 3, CvType.CV_32F); // dummy camera matrix
    intrinsics.put(0, 0, 400);
    intrinsics.put(1, 1, 400);
    intrinsics.put(0, 2, 640 / 2);
    intrinsics.put(1, 2, 480 / 2);
    Calib3d.solvePnPRansac(goodReferencePoints, goodScenePoints, intrinsics, new MatOfDouble(), mRMat, mTVec);
    MatOfDouble rotCameraMatrix1 = new MatOfDouble(3, 1, CvType.CV_32F);
    double[] rVecArray = mRMat.toArray();
    // Calib3d.Rodrigues(mRMat, rotCameraMatrix1);
    double[] tVecArray = mTVec.toArray();

    MatOfDouble projMatrix = new MatOfDouble(3, 4, CvType.CV_32F); //projMatrix 3x4 input projection matrix P.
    projMatrix.put(0, 0, rVecArray[0]);
    projMatrix.put(0, 1, rVecArray[1]);
    projMatrix.put(0, 2, rVecArray[2]);
    projMatrix.put(0, 3, 0);
    projMatrix.put(1, 0, rVecArray[3]);
    projMatrix.put(1, 1, rVecArray[4]);
    projMatrix.put(1, 2, rVecArray[5]);
    projMatrix.put(1, 3, 0);
    projMatrix.put(2, 0, rVecArray[6]);
    projMatrix.put(2, 1, rVecArray[7]);
    projMatrix.put(2, 2, rVecArray[8]);
    projMatrix.put(2, 3, 0);

    MatOfDouble cameraMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //cameraMatrix Output 3x3 camera matrix K.
    MatOfDouble rotMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrix Output 3x3 external rotation matrix R.
    MatOfDouble transVect = new MatOfDouble(4, 1, CvType.CV_32F); //transVect Output 4x1 translation vector T.
    MatOfDouble rotMatrixX = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixX a rotMatrixX
    MatOfDouble rotMatrixY = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixY a rotMatrixY
    MatOfDouble rotMatrixZ = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixZ a rotMatrixZ
    MatOfDouble eulerAngles = new MatOfDouble(3, 1, CvType.CV_32F); //eulerAngles Optional three-element vector containing three Euler angles of rotation in degrees.

    Calib3d.decomposeProjectionMatrix( projMatrix,
            cameraMatrix,
            rotMatrix,
            transVect,
            rotMatrixX,
            rotMatrixY,
            rotMatrixZ,
            eulerAngles);

    double[] eulerArray = eulerAngles.toArray(); // This has just value 0 !!!!
}

Online estimation of euler angels (camera pose) using images from camera and opencv library

I'm working on a android application and I need to estimate online camera rotation in 3D-plan using images from camera and opencv library. I like to calculate Euler angles.

I have read this and this page and I can estimate homography matrix like here.

My first question is, should I really know the camera intrinsic matrix from camera calibrtion or is the homography matrix (camera extrinsic) enough to estimate euler angles (pitch, roll, yaw)?

If homography matrix is enough, how can I do it exactly?

Sorry, I am really beginner with opencv and cannot decompose "Mat" of homography to rotation matrix and translation matrix like describes here. How can I implement euler angles in android?

This is my code, but i it return a null-vector for double[] eulerArray!!! Can somebody help me?! Thank you very much for any response!

 public void double[] findEulerAngles(MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfDMatch matches){

 KeyPoint[] k1 = keypoints1.toArray();
 KeyPoint[] k2 = keypoints2.toArray();

  List<DMatch> matchesList = matches.toList();
 List<KeyPoint> referenceKeypointsList = keypoints2.toList();
 List<KeyPoint> sceneKeypointsList = keypoints1.toList();
 // Calculate the max and min distances between keypoints.
 double maxDist = 0.0;
 double minDist = Double.MAX_VALUE;
 for(DMatch match : matchesList) {
     double dist = match.distance;
     if (dist < minDist) {
         minDist = dist;
     }
     if (dist > maxDist) {
         maxDist = dist;
     }
 }

 // Identify "good" keypoints based on match distance.
 List<Point3> goodReferencePointsList = new ArrayList<Point3>();
 ArrayList<Point> goodScenePointsList = new ArrayList<Point>();
 double maxGoodMatchDist = 1.75 * minDist;
 for(DMatch match : matchesList) {
     if (match.distance < maxGoodMatchDist) {
         Point kk2 = k2[match.queryIdx].pt;
         Point kk1 = k1[match.trainIdx].pt;

         Point3 point3 = new Point3(kk1.x, kk1.y, 0.0);
         goodReferencePointsList.add(point3);
         goodScenePointsList.add( kk2);
        sceneKeypointsList.get(match.queryIdx).pt);
    }
 }


 if (goodReferencePointsList.size() < 4 || goodScenePointsList.size() < 4) {
     // There are too few good points to find the pose.
     return;
 }

 MatOfPoint3f goodReferencePoints = new MatOfPoint3f();
 goodReferencePoints.fromList(goodReferencePointsList);
 MatOfPoint2f goodScenePoints = new MatOfPoint2f();
 goodScenePoints.fromList(goodScenePointsList);

 MatOfDouble mRMat = new MatOfDouble(3, 3, CvType.CV_32F);
 MatOfDouble mTVec = new MatOfDouble(3, 1, CvType.CV_32F);

 //TODO: solve camera intrinsic matrix
 Mat intrinsics = Mat.eye(3, 3, CvType.CV_32F); // dummy camera matrix
 intrinsics.put(0, 0, 400);
 intrinsics.put(1, 1, 400);
 intrinsics.put(0, 2, 640 / 2);
 intrinsics.put(1, 2, 480 / 2);
 Calib3d.solvePnPRansac(goodReferencePoints, goodScenePoints, intrinsics, new MatOfDouble(), mRMat, mTVec);
 MatOfDouble rotCameraMatrix1 = new MatOfDouble(3, 1, CvType.CV_32F);
 double[] rVecArray = mRMat.toArray();
 // Calib3d.Rodrigues(mRMat, rotCameraMatrix1);
 double[] tVecArray = mTVec.toArray();

 MatOfDouble projMatrix = new MatOfDouble(3, 4, CvType.CV_32F); //projMatrix 3x4 input projection matrix P.
 projMatrix.put(0, 0, rVecArray[0]);
 projMatrix.put(0, 1, rVecArray[1]);
 projMatrix.put(0, 2, rVecArray[2]);
 projMatrix.put(0, 3, 0);
 projMatrix.put(1, 0, rVecArray[3]);
 projMatrix.put(1, 1, rVecArray[4]);
 projMatrix.put(1, 2, rVecArray[5]);
 projMatrix.put(1, 3, 0);
 projMatrix.put(2, 0, rVecArray[6]);
 projMatrix.put(2, 1, rVecArray[7]);
 projMatrix.put(2, 2, rVecArray[8]);
 projMatrix.put(2, 3, 0);

 MatOfDouble cameraMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //cameraMatrix Output 3x3 camera matrix K.
 MatOfDouble rotMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrix Output 3x3 external rotation matrix R.
 MatOfDouble transVect = new MatOfDouble(4, 1, CvType.CV_32F); //transVect Output 4x1 translation vector T.
 MatOfDouble rotMatrixX = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixX a rotMatrixX
 MatOfDouble rotMatrixY = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixY a rotMatrixY
 MatOfDouble rotMatrixZ = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixZ a rotMatrixZ
 MatOfDouble eulerAngles = new MatOfDouble(3, 1, CvType.CV_32F); //eulerAngles Optional three-element vector containing three Euler angles of rotation in degrees.

 Calib3d.decomposeProjectionMatrix( projMatrix,
         cameraMatrix,
         rotMatrix,
         transVect,
         rotMatrixX,
         rotMatrixY,
         rotMatrixZ,
         eulerAngles);

 double[] eulerArray = eulerAngles.toArray(); // This has just value 0 !!!!
}
eulerAngles.toArray();

return eulerArray;

}

Online estimation of euler angels (camera pose) using images from camera and opencv library

I'm working on a android application and I need to estimate online camera rotation in 3D-plan using images from camera and opencv library. I like to calculate Euler angles.

I have read this and this page and I can estimate homography matrix like here.

My first question is, should I really know the camera intrinsic matrix from camera calibrtion or is the homography matrix (camera extrinsic) enough to estimate euler angles (pitch, roll, yaw)?

If homography matrix is enough, how can I do it exactly?

Sorry, I am really beginner with opencv and cannot decompose "Mat" of homography to rotation matrix and translation matrix like describes here. How can I implement euler angles in android?

This is You can see my code, but i code using solvePnPRansac() and decomposeProjectionMatrix to calculate euler angles. But it return returns just a null-vector for as double[] eulerArray!!! eulerArray = {0,0,0}!!! Can somebody help me?! me?! What is wrong there? Thank you very much for any response!

public double[] findEulerAngles(MatOfKeyPoint keypoints1, MatOfKeyPoint keypoints2, MatOfDMatch matches){

KeyPoint[] k1 = keypoints1.toArray();
KeyPoint[] k2 = keypoints2.toArray();


List<DMatch> matchesList = matches.toList();
List<KeyPoint> referenceKeypointsList = keypoints2.toList();
List<KeyPoint> sceneKeypointsList = keypoints1.toList();
// Calculate the max and min distances between keypoints.
double maxDist = 0.0;
double minDist = Double.MAX_VALUE;
for(DMatch match : matchesList) {
    double dist = match.distance;
    if (dist < minDist) {
        minDist = dist;
    }
    if (dist > maxDist) {
        maxDist = dist;
    }
}

// Identify "good" keypoints based on match distance.
List<Point3> goodReferencePointsList = new ArrayList<Point3>();
ArrayList<Point> goodScenePointsList = new ArrayList<Point>();
double maxGoodMatchDist = 1.75 * minDist;
for(DMatch match : matchesList) {
    if (match.distance < maxGoodMatchDist) {
        Point kk2 = k2[match.queryIdx].pt;
        Point kk1 = k1[match.trainIdx].pt;

        Point3 point3 = new Point3(kk1.x, kk1.y, 0.0);
        goodReferencePointsList.add(point3);
        goodScenePointsList.add( kk2);
        sceneKeypointsList.get(match.queryIdx).pt);
    }
}


if (goodReferencePointsList.size() < 4 || goodScenePointsList.size() < 4) {
    // There are too few good points to find the pose.
    return;
}

MatOfPoint3f goodReferencePoints = new MatOfPoint3f();
goodReferencePoints.fromList(goodReferencePointsList);
MatOfPoint2f goodScenePoints = new MatOfPoint2f();
goodScenePoints.fromList(goodScenePointsList);

MatOfDouble mRMat = new MatOfDouble(3, 3, CvType.CV_32F);
MatOfDouble mTVec = new MatOfDouble(3, 1, CvType.CV_32F);

//TODO: solve camera intrinsic matrix
Mat intrinsics = Mat.eye(3, 3, CvType.CV_32F); // dummy camera matrix
intrinsics.put(0, 0, 400);
intrinsics.put(1, 1, 400);
intrinsics.put(0, 2, 640 / 2);
intrinsics.put(1, 2, 480 / 2);
Calib3d.solvePnPRansac(goodReferencePoints, goodScenePoints, intrinsics, new MatOfDouble(), mRMat, mTVec);
MatOfDouble rotCameraMatrix1 = new MatOfDouble(3, 1, CvType.CV_32F);
double[] rVecArray = mRMat.toArray();
// Calib3d.Rodrigues(mRMat, rotCameraMatrix1);
double[] tVecArray = mTVec.toArray();

MatOfDouble projMatrix = new MatOfDouble(3, 4, CvType.CV_32F); //projMatrix 3x4 input projection matrix P.
projMatrix.put(0, 0, rVecArray[0]);
projMatrix.put(0, 1, rVecArray[1]);
projMatrix.put(0, 2, rVecArray[2]);
projMatrix.put(0, 3, 0);
projMatrix.put(1, 0, rVecArray[3]);
projMatrix.put(1, 1, rVecArray[4]);
projMatrix.put(1, 2, rVecArray[5]);
projMatrix.put(1, 3, 0);
projMatrix.put(2, 0, rVecArray[6]);
projMatrix.put(2, 1, rVecArray[7]);
projMatrix.put(2, 2, rVecArray[8]);
projMatrix.put(2, 3, 0);

MatOfDouble cameraMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //cameraMatrix Output 3x3 camera matrix K.
MatOfDouble rotMatrix = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrix Output 3x3 external rotation matrix R.
MatOfDouble transVect = new MatOfDouble(4, 1, CvType.CV_32F); //transVect Output 4x1 translation vector T.
MatOfDouble rotMatrixX = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixX a rotMatrixX
MatOfDouble rotMatrixY = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixY a rotMatrixY
MatOfDouble rotMatrixZ = new MatOfDouble(3, 3, CvType.CV_32F); //rotMatrixZ a rotMatrixZ
MatOfDouble eulerAngles = new MatOfDouble(3, 1, CvType.CV_32F); //eulerAngles Optional three-element vector containing three Euler angles of rotation in degrees.

Calib3d.decomposeProjectionMatrix( projMatrix,
        cameraMatrix,
        rotMatrix,
        transVect,
        rotMatrixX,
        rotMatrixY,
        rotMatrixZ,
        eulerAngles);

double[] eulerArray = eulerAngles.toArray();

return eulerArray;

}