OpenCV - SURF Hessian minimum threshold

c++ opencv feature-detection surf hessian-matrix
Fabrizio Duroni picture Fabrizio Duroni · Sep 11, 2013 · Viewed 15.4k times · Source

I'm working on a OpenCV project using surf to detect feature from images. The detector is initialized in this way

int minHessian = 100;

SurfFeatureDetector detector( minHessian );

Can someone explain me the meaning of the hessian threshold (in a mathematics and practice way)?

Answer

devrobf picture devrobf · Sep 19, 2013

This is explained in the SURF paper, which you should really read before using it. The SURF algorithm really contains two parts: interest point detection, and a descriptor. The Hessian corner detector is used for interest point detection in this case. The threshold determines how large the output from the Hessian filter must be in order for a point to be used as an interest point. A larger value will result in fewer, but (theoretically) more salient interest points, whereas a smaller value will result in more numerous but less salient points.

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