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Is it possible to generate key points from points tracked optical flow?

asked 2013-03-19 07:37:53 -0500

axjensen gravatar image


I'm wondering if it is possible to generate KeyPoints from the 2D location tracked by a optical flow algorithm, such as calcOpticalFlowPyrLK?

I would like to eventually extract features at the 2D location of the tracked points, by they are merely 2D points and not KeyPoints, and therefor not suitable for OpenCV's DescriptorExtractor.

I could, of course, just initialize the KeyPoints from the 2D locations, but then I cannot initialize them with values. such as angle, size etc., which would influence the quality of the features.


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answered 2013-03-19 08:18:44 -0500

Guanta gravatar image

Several ideas:

  1. First I would try your idea and initialize the 2D locations and initially assume no rotation and a scale of 1.0. If you like you can then add more keypoints at the same locations but with different scale (see e.g. how it is done in the dense-detector: detectors.cpp, l.162) and / or rotation parameters and see how good the features will match / be useful for classification.

  2. The most feature-detectors first detect 'robust' keypoints like corners. And from these ones they compute the major orientation / scale. So you could look in the source code of your favorite descriptor and modify it such that it uses your points instead of the original points of interest and then continue processing.

  3. Maybe this is possible for you: Take a window around each of your points and run OpenCV's keypoint-detector / descriptor then of course you'll most certainly get more keypoints/descriptors.

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Thank you, Guanta. I'm sticking with solution 1. It seems to work nicely. I'm now just naivly copying the intitial 2D locations properties to the tracked points.

axjensen gravatar imageaxjensen ( 2013-03-20 02:02:18 -0500 )edit
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Asked: 2013-03-19 07:37:53 -0500

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Last updated: Mar 19 '13