I. Using one of the affine invariant descriptors (MSER + SURF)
。Having better result than just using SIFT descriptor, but need to be tuned because of having only few
features which the number is less than a hundred
II. Summary of discussion
。Need to try every well-known affine invariant descriptor (especially using the proposed source code) to
find which method can provided better matching results in our datasets.
。Do more literature review & find source code of method which are using these affine invariant descriptors
。The essence of this testing experiment (or testing) is finding the method which does well in rotation,
translation, scaling (...affine transformation is not a serious problem in our work)
。For each source code (or/and the affine invariant descriptors), need to know when it does well, why it
works, and how it works (especially pay attention to the size of the descriptor / the measurement of
similarity / why parts of content in the frame doesn't show any features such as the corner of cabinet)
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