How to constrain RANSAC when using findHomography? object detection

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I want to do the matching between images, I have used SIFT as the feature and use RANSAC for improve the matching. Some results are good, but some failed. Can anyone tell me how to improve it? I think my implementation should be right as I got some good results.

The steps I do the experiment are:

Step1: Extract SIFT feature;

Step2: Use FlannBasedMatcher to do the matching;

Step3: Use RANSAC to correct the matching; // but I found too many points are matched to a single point

Below are the core code for my experiment:

 FlannBasedMatcher matcher; 

 std::vector< DMatch > matches;  

 matcher.match( descriptors_1, descriptors_2, matches );  

 double max_dist = 0;   
 double min_dist = 100;  

 for( int i = 0; i < descriptors_1.rows; i++ )  
{   
    double dist = matches[i].distance;  
    if( dist < min_dist ) min_dist = dist;  
    if( dist > max_dist ) max_dist = dist;  
}  
for( int i = 0; i < descriptors_1.rows; i++ )  
{   
    if( matches[i].distance < max_dist)
    {   
        good_matches.push_back( matches[i]);   //keep all the matches
    }  
}  

H = findHomography( tmp_obj, tmp_scene, CV_RANSAC, 3.0, Mask); 

    for (int i = 0; i< good_matches.size(); i ++)
    {

        if (Mask.at<uchar>(i) != 0)  // RANSAC selection
        {


            obj.push_back( keypoints_object[ good_matches[i].queryIdx ].pt );  
            scene.push_back( keypoints_scene[ good_matches[i].trainIdx ].pt );   

            good_matches2.push_back(good_matches[i]);

            numGood = numGood + 1;

        }

    }

some failed case: