BRIEF: Binary Robust Independent Elementary Features
What is this? BRIEF is a general-purpose feature point descriptor that can be combined
with arbitrary detectors. It is robust to typical classes of photometric
and geometric image transformations. BRIEF is targeting real-time
applications leaving them with a large portion of the available CPU power
for subsequent tasks but also allows running feature point matching algorithms on
computationally weak devices such as mobile phones. For details including
comparisons to the state-of-the-art, please refer to the paper.
Accuracy. Comparing BRIEF with OpenCV SURF
on standard Wall (left) and
Fountain datasets. The
plots show the recognition rate (accuracy) for U-SURF-64 and BRIEF-32 versus five image
pairs of the respective image sequence. 1000 points were matched for each image pair.
click to enlarge
click to enlarge
Speed. Owing to its salient simplicity, BRIEF is extremely
efficient to compute which results in a speed-up of almost two orders of magnitude over
U-SURF-64. Compared to a recent GPU implementation of SURF, BRIEF-32P is still
about 4 times faster to compute while using a single 2.53 GHz CPU. The timings
are the median values obtained from 10 runs of a standard detect-describe-match cycle.
click to enlarge
Software
Note on Efficient Distance Computations.
Computing the Hamming distance between two binary vectors
corresponds to a simple bitcount on the result of a binary XOR
operation between the vectors. The bitcount becomes
particularly efficient on CPUs supporting the POPCNT
instruction: The first in this series are Intel's Bloomfield (SSE 4.2) and AMD's Phenom (SSE 4a). If your CPU supports this instruction, you can safely;
enable -msse4.2 (or -msse4a, respectively)
in test_app/Makefile. This should give you a
10- to 15-fold speed increase for matching. If enabled
despite SSE 4.2 (SSE 4a, respectively) is not supported, you will
get an Illegal instruction. On linux, try grep sse
/proc/cpuinfo and look for sse4_2 (or
sse4a, respectively) to find out whether or not
POPCNT is available on your machine.
BRIEF: Binary Robust Independent Elementary Features
M. Calonder, V. Lepetit, C. Strecha, P. Fua
ECCV 2010 pdf
|
@inproceedings{calonder10-brief,
author = {M. Calonder and V. Lepetit and C. Strecha and P. Fua},
title = {{BRIEF: Binary Robust Independent Elementary Features}},
booktitle = {European Conference on Computer Vision},
month = 9,
year = 2010,
}
