Best matching strategy

asked 2014-04-28 07:06:07 -0600

jpl gravatar image

why is the majority of articles which compare feature descriptors choose to use as a matching strategy K nearest neighbor+ransac instead of bruteforcematcher+a threshold? Are there adavantages of using the first method over the second?

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I don't know enough to give you all the pros/cons between those two. There are many new articles about newer detectors, however it all depends on what you are trying to detect and what the situation is. In my case the camera is in a fixed place and the target image is provided so I went with match template and used a background scan to try different sizes and rotations. I then added a sub pixel routine to increase the accuracy.

GrumbleLion gravatar imageGrumbleLion ( 2014-04-28 14:48:14 -0600 )edit