Package org.opencv.xfeatures2d
Class BoostDesc
java.lang.Object
org.opencv.core.Algorithm
org.opencv.features2d.Feature2D
org.opencv.xfeatures2d.BoostDesc
Class implementing BoostDesc (Learning Image Descriptors with Boosting), described in
CITE: Trzcinski13a and CITE: Trzcinski13b.
desc type of descriptor to use, BoostDesc::BINBOOST_256 is default (256 bit long dimension)
Available types are: BoostDesc::BGM, BoostDesc::BGM_HARD, BoostDesc::BGM_BILINEAR, BoostDesc::LBGM,
BoostDesc::BINBOOST_64, BoostDesc::BINBOOST_128, BoostDesc::BINBOOST_256
use_orientation sample patterns using keypoints orientation, enabled by default
scale_factor adjust the sampling window of detected keypoints
6.25f is default and fits for KAZE, SURF detected keypoints window ratio
6.75f should be the scale for SIFT detected keypoints window ratio
5.00f should be the scale for AKAZE, MSD, AGAST, FAST, BRISK keypoints window ratio
0.75f should be the scale for ORB keypoints ratio
1.50f was the default in original implementation
Note: BGM is the base descriptor where each binary dimension is computed as the output of a single weak learner.
BGM_HARD and BGM_BILINEAR refers to same BGM but use different type of gradient binning. In the BGM_HARD that
use ASSIGN_HARD binning type the gradient is assigned to the nearest orientation bin. In the BGM_BILINEAR that use
ASSIGN_BILINEAR binning type the gradient is assigned to the two neighbouring bins. In the BGM and all other modes that use
ASSIGN_SOFT binning type the gradient is assigned to 8 nearest bins according to the cosine value between the gradient
angle and the bin center. LBGM (alias FP-Boost) is the floating point extension where each dimension is computed
as a linear combination of the weak learner responses. BINBOOST and subvariants are the binary extensions of LBGM
where each bit is computed as a thresholded linear combination of a set of weak learners.
BoostDesc header files (boostdesc_*.i) was exported from original binaries with export-boostdesc.py script from
samples subfolder.
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Field Summary
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionstatic BoostDesc
__fromPtr__
(long addr) static BoostDesc
create()
static BoostDesc
create
(int desc) static BoostDesc
create
(int desc, boolean use_scale_orientation) static BoostDesc
create
(int desc, boolean use_scale_orientation, float scale_factor) protected void
finalize()
Returns the algorithm string identifier.float
boolean
void
setScaleFactor
(float scale_factor) void
setUseScaleOrientation
(boolean use_scale_orientation) Methods inherited from class org.opencv.features2d.Feature2D
compute, compute, defaultNorm, descriptorSize, descriptorType, detect, detect, detect, detect, detectAndCompute, detectAndCompute, empty, read, write
Methods inherited from class org.opencv.core.Algorithm
clear, getNativeObjAddr, save
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Constructor Details
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BoostDesc
protected BoostDesc(long addr)
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Method Details
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__fromPtr__
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create
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create
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create
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create
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getDefaultName
Description copied from class:Algorithm
Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.- Overrides:
getDefaultName
in classFeature2D
- Returns:
- automatically generated
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setUseScaleOrientation
public void setUseScaleOrientation(boolean use_scale_orientation) -
getUseScaleOrientation
public boolean getUseScaleOrientation() -
setScaleFactor
public void setScaleFactor(float scale_factor) -
getScaleFactor
public float getScaleFactor() -
finalize
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