OpenCV Feature Note(IV) BRIEF

Paper:

http://www.gwylab.com/download/BRIEF_2010.pdf

Trait

BRIEF algorithm is a descriptor algorithm, not like SIFT/SURF

1. BRIEF does not care about how to find potential corners
2. BRIEF only contains a descriptor design
3. BRIEF can be combined with FAST keypoints result

BRIEF essential is SOLVING THE MEMORY PROBLEM

like the document said SIFT/SURF ..

"Creating such a vector for thousands of features takes a lot of memory which are not feasible for resource-constraint applications especially for embedded systems."

How

How to save the memory ?

1. Replace calculate float number by compare with binary stream Hamming Distance.
2. Not generate too complicated descriptor in memory

method1 is also useful in SIFT/SURF process, BUT …

"we need to find the descriptors first, then only can we apply hashing, which doesn't solve our initial problem on memory."

method2 actually solve the memory problem

there are 3 main steps refer from official document

1. selects a set of nd (x,y) location pairs around keypoint in a unique way
2. compre the point p,q pixel intensity in each pair, an record the result with 0/1
3. take the result binary stream(binary string) as a descriptor

about the “around”

1. in paper it define as S x S area
2. in openCV which default value S = 31

about the “unique way” detail can be explained in paper, in summary

1. mean value sample
2. p,q obey same gauss distribution sample
3. p,q obey different gauss distribution sample
4. use polar coordinate system
5. p is fix to (0,0) then q around to p

Orientation Sensitivity:

From paper we can know

"BRIEF is not designed to be rotationally invariant....it tolerates small amounts of rotation"

from experience if rotate angle should less than 30 degree

IN CONCLUSION:

BRIEF descriptor not use the data as a descriptor, using the result calculate by data as descriptor

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请问老板还招人么(/ω＼)

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