I am working on ear Recognition project. I have database of ears, 60 person - each 4 ears. What I have already done, is that I detectAndCompute from each image Descriptors and Keypoints. Now I need to compare each image with each and find the best result.
What I did is that, I used BFMacther which returns matches [link text](http://docs.opencv.org/3.0-beta/doc/py_tutorials/py_feature2d/py_matcher/py_matcher.html) .
The larger the vector is, the difference between the images is smaller and are more similar right? So I saved the largest vector in comparison in one image with every other image and that is the result as the largest vector?
I am thinking now about second maybe better options?
I also found out, that is BFMatcher has method to train. So I can add every train Descriptors to BFMatcher and then call train.
But now when I have trained BFMatcher how can I compare and get the result of my test vector?
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