Hi there, I attempt to compare two images with SURF and FLANN. The first image is basically the first frame captured of a camera when you run the app. The other image change at every frame since it is a video stream.
So my first frame is the reference, and I compare it to the other frames I get further.
So first I use xfeatures2d.SURF_create(hessianThreshold=NUMBER) to instanciate surf, and then I use FlannBasedMatcher(index_params, search_params) where index_params = dict(algorithme=KDTREE, trees=NUMBER) and search_params = dict(checks=NUMBER).
I just want to have some explanations about these parameters, for exemple, is it better to increase or decrease the trees, or the checks ? Because I don’t find any explanations on the doc.
Also, is this the best way to compare the two images for camera tampering detection ? Because the camera can switch from color mode to infra red mode so SURF doesn’t seems to support the switch. However, when it is the same color mode, SURF seems to cover all the usecases (like the camera movement, over or under exposed, etc). So what is your opinion on this choice ?