title: BRIEF: Computing a Local Binary Descriptor Very Fast.
abstract: Binary descriptors are becoming increasingly popular as a means to compare feature points very fast 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, which 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.
authors.affiliation: Computer Vision Laboratory, I&C Faculty, Ecole Polytechnique Fe´de´rale de Lausanne (EPFL), Lausanne CH-1015, Switzerland. michael.calonder@a3.epfl.ch
authors.forename: Michael
authors.initials: M
authors.lastname: Calonder
authors.forename: Vincent
authors.initials: V
authors.lastname: Lepetit
authors.forename: Mustafa
authors.initials: M
authors.lastname: Özuysal
authors.forename: Tomasz
authors.initials: T
authors.lastname: Trzcinski
authors.forename: Christoph
authors.initials: C
authors.lastname: Strecha
authors.forename: Pascal
authors.initials: P
authors.lastname: Fua