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BRIEF: Computing a Local Binary Descriptor Very Fast

Calonder, Michael  
•
Lepetit, Vincent  
•
Özuysal, Mustafa  
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2012
IEEE Transactions on Pattern Analysis and Machine Intelligence

Binary descriptors are becoming increasingly popular as a means to compare feature points very fast and while requiring comparatively small amounts of memory. The typical approach to creating them is to first compute floating-point ones, using an algorithm such as SIFT, and then to binarize them. In this paper, we show that we can directly compute a binary descriptor we call BRIEF on the basis of simple intensity difference tests. As a result, BRIEF is very fast both to build and to match. We compare it against SURF and SIFT on standard benchmarks and show that it yields comparable recognition accuracy, while running in an almost vanishing fraction of the time required by either.

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