The input arrays should be 2D or 3D point sets in function 'findHomography'

Question

I have used Feature Matching and Homography to find objects in a scene. I have followed the tutorial of the docs. I will put first code and exceptions and at the end I will post the images.

Code:

 String filenameObject = args.length > 1 ? args[0] : "./test/test1.png";
    String filenameScene = args.length > 1 ? args[1] : "./screenshots/test2.jpg";
    Mat imgObject = Imgcodecs.imread(filenameObject, Imgcodecs.IMREAD_GRAYSCALE);
    Mat imgScene = Imgcodecs.imread(filenameScene, Imgcodecs.IMREAD_GRAYSCALE);
    if (imgObject.empty() || imgScene.empty()) {
        System.err.println("Cannot read images!");
        System.exit(0);
    }
    //-- Step 1: Detect the keypoints using SURF Detector, compute the descriptors
    double hessianThreshold = 400;
    int nOctaves = 4, nOctaveLayers = 3;
    boolean extended = false, upright = false;
    SURF detector = SURF.create(hessianThreshold, nOctaves, nOctaveLayers, extended, upright);
    MatOfKeyPoint keypointsObject = new MatOfKeyPoint(), keypointsScene = new MatOfKeyPoint();
    Mat descriptorsObject = new Mat(), descriptorsScene = new Mat();
    detector.detectAndCompute(imgObject, new Mat(), keypointsObject, descriptorsObject);
    detector.detectAndCompute(imgScene, new Mat(), keypointsScene, descriptorsScene);
    //-- Step 2: Matching descriptor vectors with a FLANN based matcher
    // Since SURF is a floating-point descriptor NORM_L2 is used
    DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.FLANNBASED);
    List<MatOfDMatch> knnMatches = new ArrayList<>();
    matcher.knnMatch(descriptorsObject, descriptorsScene, knnMatches, 2);
    //-- Filter matches using the Lowe's ratio test
    float ratioThresh = 0.75f;
    List<DMatch> listOfGoodMatches = new ArrayList<>();
    for (int i = 0; i < knnMatches.size(); i++) {
        if (knnMatches.get(i).rows() > 1) {
            DMatch[] matches = knnMatches.get(i).toArray();
            if (matches[0].distance < ratioThresh * matches[1].distance) {
                listOfGoodMatches.add(matches[0]);
            }
        }
    }
    MatOfDMatch goodMatches = new MatOfDMatch();
    goodMatches.fromList(listOfGoodMatches);
    //-- Draw matches
    Mat imgMatches = new Mat();
    Features2d.drawMatches(imgObject, keypointsObject, imgScene, keypointsScene, goodMatches, imgMatches, Scalar.all(-1),
            Scalar.all(-1), new MatOfByte(), Features2d.DrawMatchesFlags_NOT_DRAW_SINGLE_POINTS);
    //-- Localize the object
    List<Point> obj = new ArrayList<>();
    List<Point> scene = new ArrayList<>();
    List<KeyPoint> listOfKeypointsObject = keypointsObject.toList();
    List<KeyPoint> listOfKeypointsScene = keypointsScene.toList();
    for (int i = 0; i < listOfGoodMatches.size(); i++) {
        //-- Get the keypoints from the good matches
        obj.add(listOfKeypointsObject.get(listOfGoodMatches.get(i).queryIdx).pt);
        scene.add(listOfKeypointsScene.get(listOfGoodMatches.get(i).trainIdx).pt);
    }
    MatOfPoint2f objMat = new MatOfPoint2f(), sceneMat = new MatOfPoint2f();
    objMat.fromList(obj);
    sceneMat.fromList(scene);
    double ransacReprojThreshold = 3.0;
    Mat H = Calib3d.findHomography( objMat, sceneMat, Calib3d.RANSAC, ransacReprojThreshold );
    //-- Get the corners from the image_1 ( the object to be "detected" )
    Mat objCorners = new Mat(4, 1, CvType.CV_32FC2), sceneCorners = new Mat();
    float[] objCornersData = new float[(int) (objCorners.total() * objCorners.channels())];
    objCorners.get(0, 0, objCornersData);
    objCornersData[0] = 0;
    objCornersData[1] = 0;
    objCornersData[2] = imgObject.cols();
    objCornersData[3] = 0;
    objCornersData[4] = imgObject.cols();
    objCornersData[5] = imgObject.rows();
    objCornersData[6] = 0;
    objCornersData[7] = imgObject.rows();
    objCorners.put(0, 0, objCornersData);
    Core.perspectiveTransform(objCorners, sceneCorners, H);
    float[] sceneCornersData = new float[(int) (sceneCorners.total() * sceneCorners.channels())];
    sceneCorners.get(0, 0, sceneCornersData);
    //-- Draw lines between the corners (the mapped object in the scene - image_2 )
    Imgproc.line(imgMatches, new Point(sceneCornersData[0] + imgObject.cols(), sceneCornersData[1]),
            new Point(sceneCornersData[2] + imgObject.cols(), sceneCornersData[3]), new Scalar(0, 255, 0), 4);
    Imgproc.line(imgMatches, new Point(sceneCornersData[2] + imgObject.cols(), sceneCornersData[3]),
            new Point(sceneCornersData[4] + imgObject.cols(), sceneCornersData[5]), new Scalar(0, 255, 0), 4);
    Imgproc.line(imgMatches, new Point(sceneCornersData[4] + imgObject.cols(), sceneCornersData[5]),
            new Point(sceneCornersData[6] + imgObject.cols(), sceneCornersData[7]), new Scalar(0, 255, 0), 4);
    Imgproc.line(imgMatches, new Point(sceneCornersData[6] + imgObject.cols(), sceneCornersData[7]),
            new Point(sceneCornersData[0] + imgObject.cols(), sceneCornersData[1]), new Scalar(0, 255, 0), 4);
    //-- Show detected matches
    HighGui.imshow("Good Matches & Object detection", imgMatches);
    Imgcodecs.imwrite("result/SURFFLANNMatchingHomography.jpg", imgMatches);
    HighGui.waitKey(0);
    System.exit(0);

I get the two following exceptions:

Exception in thread "main" CvException [org.opencv.core.CvException: cv::Exception: OpenCV(4.7.0) /tmp/opencv-20230625-23894-1o8sdu5/opencv-4.7.0/modules/calib3d/src/fundam.cpp:378: error: (-5:Bad argument) The input arrays should be 2D or 3D point sets in function 'findHomography'

or

  Exception in thread "main" CvException [org.opencv.core.CvException: cv::Exception: OpenCV(4.7.0) /tmp/opencv-20230625-23894-1o8sdu5/opencv-4.7.0/modules/calib3d/src/fundam.cpp:385: error: (-28:Unknown error code -28) The input arrays should have at least 4 corresponding point sets to calculate Homography in function 'findHomography'

I need to detect object that aren't that much complex: pokestops.

Some images of the object I am trying to detect:

Screenshots of where I want to detect that type of object: