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ORB number of keypoints

asked 2014-06-16 10:04:07 -0500

juanarocha gravatar image

OpenCV OrbFeatureDetector's detect function has a parameter nFeatures which tells the function what is the maximum number of keypoints to be detected.

I know more points means more comparisons when matching so less performance, while less means less accuracy.

Is there a recommended number of keypoints that gives me a good accuracy/performance relation? And if there is, why?

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answered 2014-06-16 10:58:48 -0500

Depends on the application. Also, it depends on the specific image (a lot of texture and corners vs. a smooth image). I think a better approach would be to detect a large number of keypoints and delete all the keypoints with response below a threshold.

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Yes that's what I normally do. With 1500 (as is done in OpenCV examples) and then thresholding, but I've seen some posts recommending 300-400 points. So, I was wondering if there's some kind of standard or recommended values. ORB's paper doesn't say anything about it

juanarocha gravatar imagejuanarocha ( 2014-06-16 11:49:57 -0500 )edit

In my opinion, there shouldn't be a global standard, as it varies from image to image and from application to application.

GilLevi gravatar imageGilLevi ( 2014-06-16 13:34:16 -0500 )edit

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Asked: 2014-06-16 10:04:07 -0500

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Last updated: Jun 16 '14