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Erschienen in:
2010 | OriginalPaper | Buchkapitel
BRIEF: Binary Robust Independent Elementary Features
verfasst von : Michael Calonder, Vincent Lepetit, Christoph Strecha, Pascal Fua
Erschienen in: Computer Vision – ECCV 2010
Verlag: Springer Berlin Heidelberg
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We propose to use binary strings as an efficient feature point descriptor, which we call BRIEF.We show that it is highly discriminative even when using relatively few bits and can be computed using simple intensity difference tests. Furthermore, the descriptor similarity can be evaluated using the Hamming distance, which is very efficient to compute, instead of the
L
2
norm as is usually done.
As a result, BRIEF is very fast both to build and to match. We compare it against SURF and U-SURF on standard benchmarks and show that it yields a similar or better recognition performance, while running in a fraction of the time required by either.