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videostab::estimateGlobalMotionLeastSquares() doesn't work properly

asked 2017-10-17 23:17:07 -0500

Dan Do gravatar image

updated 2017-10-19 20:42:32 -0500

Hi there,

Could any one give me an example of using videostab APIs in OpenCV-3.3.0 to estimate global motion between two adjacent frames? I couldn't find any of them, so I have figured out my way (as explained step by step bellowed). I am trying with estimateGlobalMotionLeastSquares(), but things seem doesn't work well.

Here are 2 original gray frames (left: previous, right: current) between those I want to find the global motion matrix.

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After the extraction of keypoints (using cv::goodFeatureTotrack).

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Getting transformation matrix with estimateGlobalMotionLeastSquares(), then have it transform the previous frame into coordinate space of the current one (left) and compute difference image (right).

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You can see that the result are terrible. In bellow I attach my piece of code, I would highly appreciate a help to figure out possible mistakes in it, or favorably a well working sample of code.

 //------------- READ 2 CONSECUTIVE FRAMES
 videoSrc.read(prev_frame);
 videoSrc.read(cur_frame);

 //------------- CONVERT TO GRAY SCALE & EXTRACT KEY POINTS
 cvtColor(prev_frame, prev_gray, COLOR_RGB2GRAY);
 cvtColor(cur_frame, cur_gray, COLOR_RGB2GRAY);

 goodFeaturesToTrack(prev_gray, prev_keypoints, 500, 0.04f, 10, cv::Mat(), 5, 0, 0.04f);
 goodFeaturesToTrack(cur_gray, cur_keypoints, 500, 0.04f, 10, cv::Mat(), 5, 0, 0.04f);


 //------------- ESTIMATE GLOBAL MOTION BASED ON THE ABOVE SETS OF KEY POINTS
 Mat m_transform = videostab::estimateGlobalMotionLeastSquares(prev_keypoints, cur_keypoints, videostab::MM_AFFINE, NULL);


 //------------- COMPUTE DIFFERENCE IMAGES
 Mat prev_gray_trans, diffImg, normImg;

 warpPerspective(prev_gray, prev_gray_trans, m_transform, Size(prev_gray.cols, prev_gray.rows));
 diffImg = cur_gray - prev_gray_trans;
 normalize (diffImg, normImg, 0, 255, NORM_MINMAX, CV_8UC1, Mat());
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answered 2018-03-14 21:09:53 -0500

Your 2 points sets are independent of one another. I think you need to use one of the feature matching functions:

BFMatcher() FlannBasedMatcher()

to find corresponding sets of points to pass in.

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Asked: 2017-10-17 23:15:42 -0500

Seen: 230 times

Last updated: Oct 19 '17