Android application to recognize and track object from camera has more false positives?

edit savecancel

I'm really new to openCV I followed this but detection too slow

mRgba matrix from camera input
mRef matrix from object image

FeatureDetector detector = FeatureDetector.create(FeatureDetector.ORB);
DescriptorExtractor extractor = DescriptorExtractor.create(DescriptorExtractor.ORB);
DescriptorMatcher matcher = DescriptorMatcher.create(DescriptorMatcher.BRUTEFORCE);
detector.detect(mGray, keypoints);
detector.detect(mRef, keypointsRef);     
extractor.compute(mGray, keypoints, extract);
extractor.compute(mRef, keypointsRef, extractRef);
matcher.match(extractRef, extract, matchs);
List<KeyPoint> keypoints_RefList = keypointsRef.toList();
List<KeyPoint> keypoints_List = keypoints.toList();
if (matchesList.get(i).distance <= (3 * min_dist)) {
 good_matches.addLast(matchesList.get(i));  
}
for (int i = 0; i < good_matches.size(); i++) {
  objList.addLast(keypoints_RefList.get(good_matches.get(i).queryIdx).pt);
  sceneList.addLast(keypoints_List.get(good_matches.get(i).trainIdx).pt);
}  
obj.fromList(objList);
scene.fromList(sceneList);
Mat hg = Calib3d.findHomography(obj, scene, 8, 2, new Mat());
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(1, 0, new double[] {mRef.cols(), 0});
obj_corners.put(2, 0, new double[] {mRef.cols(), mRef.rows()});
obj_corners.put(3, 0, new double[] {0, mRef.rows()});
Core.perspectiveTransform(obj_corners, scene_corners, hg);
Core.line(mRgba, new Point(scene_corners.get(0,0)), new Point(scene_corners.get(1,0)), new Scalar(0, 255, 0),3);
Core.line(mRgba, new Point(scene_corners.get(1,0)), new Point(scene_corners.get(2,0)), new Scalar(0, 255, 0),3);
Core.line(mRgba, new Point(scene_corners.get(2,0)), new Point(scene_corners.get(3,0)), new Scalar(0, 255, 0),3);
Core.line(mRgba, new Point(scene_corners.get(3,0)), new Point(scene_corners.get(0,0)), new Scalar(0, 255, 0),3);

This is way too wrong it detects almost anything as output and draws random points as output.

Is there a way to refine the detection?

Can histogram, dialate or smooth options be applied to the images?