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Cropping keypoints vs. cropping image and finding keypoints

asked 2018-01-09 22:22:36 -0500

charles1208 gravatar image

Given an image of many items, with all of its bounding box known in pixel coordinates.

I am trying to extract a region (surrounding) around each of the items, calculate its descriptors and features using AKAZE, to do comparison with one another.

However I realised that this might be too slow, since it involves:

1) cropping each and every single item to generate many images then,

2) detecting and computing on each image to generate the keypoints and descriptors.

Alternatively, to speed things up, I was thinking of:

1) Resizing the entire image, then perform the detecting and computing of keypoints once.

2) Then to obtain the keypoint of a particular object, we simply retrieve the set of precalculated keypoints corresponding to the objects location.

My question is this method functionally sound, and that if there are any consequences to this?

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answered 2018-01-09 22:44:18 -0500

Tetragramm gravatar image

The only thing to be wary of is that with a limited number of keypoints detected, it might not find very many in some areas of the image. If you crop it to just that area, then it will find the specified number of keypoints.

You can probably check each bounding box to see if there are enough points, and then lower your threshold/up the number of points until you get enough.

The actual keypoints will have the same descriptors and such though, so no problem there.

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Asked: 2018-01-09 22:22:36 -0500

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Last updated: Jan 09 '18