Image Stitching (Java API)

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Hi, I'm trying to stitch two images together, using the OpenCV Java API. I have been following this C++ tutorial here http://ramsrigoutham.com/2012/11/22/panorama-image-stitching-in-opencv/ However, I get the wrong output and I cannot work out the problem.

FAULTY CODE

public class ImageStitching {

static Mat image1;
static Mat image2;

static FeatureDetector fd;
static DescriptorExtractor fe;
static DescriptorMatcher fm;

public static void initialise(){
    fd = FeatureDetector.create(FeatureDetector.BRISK); 
    fe = DescriptorExtractor.create(DescriptorExtractor.SURF); 
    fm = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);

    //images
    image1 = Highgui.imread("room2.jpg");
    image2 = Highgui.imread("room3.jpg");

    //structures for the keypoints from the 2 images
    MatOfKeyPoint keypoints1 = new MatOfKeyPoint();
    MatOfKeyPoint keypoints2 = new MatOfKeyPoint();

    //structures for the computed descriptors
    Mat descriptors1 = new Mat();
    Mat descriptors2 = new Mat();

    //structure for the matches
    MatOfDMatch matches = new MatOfDMatch();

    //getting the keypoints
    fd.detect(image1, keypoints1);
    fd.detect(image1, keypoints2);

    //getting the descriptors from the keypoints
    fe.compute(image1, keypoints1, descriptors1);
    fe.compute(image2,keypoints2,descriptors2);

    //getting the matches the 2 sets of descriptors 
    fm.match(descriptors2,descriptors1, matches);

    //turn the matches to a list
    List<DMatch> matchesList = matches.toList();

    Double maxDist = 0.0; //keep track of max distance from the matches
    Double minDist = 100.0; //keep track of min distance from the matches

    //calculate max & min distances between keypoints
    for(int i=0; i<keypoints1.rows();i++){
        Double dist = (double) matchesList.get(i).distance;
        if (dist<minDist) minDist = dist;
        if(dist>maxDist) maxDist=dist;
    }

    System.out.println("max dist: " + maxDist );
    System.out.println("min dist: " + minDist);

    //structure for the good matches
    LinkedList<DMatch> goodMatches = new LinkedList<DMatch>();

    //use only the good matches (i.e. whose distance is less than 3*min_dist)
    for(int i=0;i<descriptors1.rows();i++){
        if(matchesList.get(i).distance<3*minDist){
            goodMatches.addLast(matchesList.get(i));
        }
    }

    //structures to hold points of the good matches (coordinates)
    LinkedList<Point> objList = new LinkedList<Point>(); // image1
    LinkedList<Point> sceneList = new LinkedList<Point>(); //image 2

    List<KeyPoint> keypoints_objectList = keypoints1.toList();
    List<KeyPoint> keypoints_sceneList = keypoints2.toList();

    //putting the points of the good matches into above structures
    for(int i = 0; i<goodMatches.size(); i++){
        objList.addLast(keypoints_objectList.get(goodMatches.get(i).queryIdx).pt);
        sceneList.addLast(keypoints_sceneList.get(goodMatches.get(i).trainIdx).pt);
    }

    System.out.println("\nNum. of good matches" +goodMatches.size());

    MatOfDMatch gm = new MatOfDMatch();
    gm.fromList(goodMatches);

    //converting the points into the appropriate data structure
    MatOfPoint2f obj = new MatOfPoint2f();
    obj.fromList(objList);

    MatOfPoint2f scene = new MatOfPoint2f();
    scene.fromList(sceneList);

    //finding the homography matrix
    Mat H = Calib3d.findHomography(obj, scene);

    //LinkedList<Point> cornerList = new LinkedList<Point>();
    Mat obj_corners = new Mat(4,1,CvType.CV_32FC2);
    Mat scene_corners = new Mat(4,1,CvType.CV_32FC2);

    obj_corners.put(0,0, new double[]{0,0});
    obj_corners.put(0,0, new double[]{image1.cols(),0});
    obj_corners.put(0,0,new double[]{image1.cols(),image1.rows()});
    obj_corners.put(0,0,new double[]{0,image1.rows()});

    Core.perspectiveTransform(obj_corners, scene_corners, H);

    //structure to hold the result of the homography matrix
    Mat result = new Mat();

    //size of the new image - i.e. image 1 + image 2
    Size s = new ...