Video Stabilization with OpenCV

Question

I have a video feed which is taken with a moving camera and contains moving objects. I would like to stabilize the video, so that all stationary objects will remain stationa

Answer 1

I can suggest one of the following solutions:

1. Using local high level features: OpenCV includes SURF, so: for each frame, extract SURF features. Then build feature Kd-Tree (also in OpenCV), then match each two consecutive frames to find pairs of corresponding features. Feed those pairs into cvFindHomography to compute the homography between those frames. Warp frames according to (combined..) homographies to stabilize. This is, to my knowledge, a very robust and sophisticated approach, however SURF extraction and matching can be quite slow
2. You can try to do the above with "less robust" features, if you expect only minor movement between two frames, e.g. use Harris corner detection and build pairs of corners closest to each other in both frames, feed to cvFindHomography then as above. Probably faster but less robust.
3. If you restrict movement to translation, you might be able to replace cvFindHomography with something more...simple, to just get the translation between feature-pairs (e.g. average)
4. Use phase-correlation (ref. http://en.wikipedia.org/wiki/Phase_correlation), if you expect only translation between two frames. OpenCV includes DFT/FFT and IFFT, see the linked wikipedia article on formulas and explanation.

EDIT Three remarks I should better mention explicitly, just in case:

1. The homography based approach is likely very exact, so stationary object will remain stationary. However, homographies include perspective distortion and zoom as well so the result might look a bit..uncommon (or even distorted for some fast movements). Although exact, this might be less visually pleasing; so use this rather for further processing or, like, forensics. But you should try it out, could be super-pleasing for some scenes/movements as well.
2. To my knowledge, at least several free video-stabilization tools use the phase-correlation. If you just want to "un-shake" the camera, this might be preferable.
3. There is quite some research going on in this field. You'll find some a lot more sophisticated approaches in some papers (although they likely require more than just OpenCV).

Answer 2

Background: I was working on this research project where I was trying to calculate that how long would it take for person standing in the queue to reach to the counter. First thing I required was FOOTAGE so I went to the campus and recorded some tourist moving in the queue to get tickets. Till this point I had not idea how would I gonna calculate queuing time and what pre-caution should I take while recording the footage. At the end of the day I found that all the footage I recorded was recorded with shaky camera. So at this point I was first required to stabilize the video and then only develop other solution to calculate queuing time.

Video Stabilization using Template Matching

• Find static objects such as poll, door or something that you know are not supposed to move
• Use template matching to calculate offset of change of location of static object(relative to the frame boundaries) in each consecutive frame.
• Translate the each frame with the offset value i.e. let's say tx and ty.

Result Footage:

Gif to show the result of this technique

As you can see in the gif that selected static object remain static w.r.t the frame boundaries while motion can be see by black filling from the edges of the frame.