How to use Mikolajczyk's evaluation framework for feature detectors/descriptors?

Question

I'm trying the assess the correctness of my SURF descriptor implementation with the de facto standard framework by Mikolajczyk et. al. I'm using OpenCV to detect and describe SURF features, and use the same feature positions as input to my descriptor implementation.

To evaluate descriptor performance, the framework requires to evaluate detector repeatability first. Unfortunately, the repeatability test expects a list of feature positions along with ellipse parameters defining the size and orientation of an image region around each feature. However, OpenCV's SURF detector only provides feature position, scale and orientation.

The related paper proposes to compute those ellipse parameters iteratively from the eigenvalues of the second moment matrix. Is this the only way? As far as I can see, this would require some fiddling with OpenCV. Is there no way to compute those ellipse parameters afterwards (e.g. in Matlab) from the feature list and the input image?

Has anyone ever worked with this framework and could assist me with some insights or pointers?

Outnumber

Answer 1

You can use the file evaluation.cpp from OpenCV. Is in the directory OpenCV/modules/features2d/src. In this file you could use the class "EllipticKeyPoint", this class has one function to convert "KeyPoint" to "ElipticKeyPoint"

Bootjack

Answer 2

Honestly I never worked with this framework., but I think you should see this paper about a performance evaluation of local descriptors.

Injurious

Thanks. I'm aware of this paper, but unfortunately it doesn't give anymore details on how to obtain the ellipse parameters. – Outnumber