public class ORB extends Feature2D
Modifier and Type | Field and Description |
---|---|
static int |
FAST_SCORE |
static int |
HARRIS_SCORE |
Modifier | Constructor and Description |
---|---|
protected |
ORB(long addr) |
Modifier and Type | Method and Description |
---|---|
static ORB |
__fromPtr__(long addr) |
static ORB |
create()
The ORB constructor
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically.
|
static ORB |
create(int nfeatures)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
int scoreType)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
int scoreType,
int patchSize)
The ORB constructor
|
static ORB |
create(int nfeatures,
float scaleFactor,
int nlevels,
int edgeThreshold,
int firstLevel,
int WTA_K,
int scoreType,
int patchSize,
int fastThreshold)
The ORB constructor
|
protected void |
finalize() |
String |
getDefaultName()
Returns the algorithm string identifier.
|
int |
getEdgeThreshold() |
int |
getFastThreshold() |
int |
getFirstLevel() |
int |
getMaxFeatures() |
int |
getNLevels() |
int |
getPatchSize() |
double |
getScaleFactor() |
int |
getScoreType() |
int |
getWTA_K() |
void |
setEdgeThreshold(int edgeThreshold) |
void |
setFastThreshold(int fastThreshold) |
void |
setFirstLevel(int firstLevel) |
void |
setMaxFeatures(int maxFeatures) |
void |
setNLevels(int nlevels) |
void |
setPatchSize(int patchSize) |
void |
setScaleFactor(double scaleFactor) |
void |
setScoreType(int scoreType) |
void |
setWTA_K(int wta_k) |
compute, compute, defaultNorm, descriptorSize, descriptorType, detect, detect, detect, detect, detectAndCompute, detectAndCompute, empty, read, write
clear, getNativeObjAddr, save
public static final int HARRIS_SCORE
public static final int FAST_SCORE
public static ORB __fromPtr__(long addr)
public int getScoreType()
public static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold, int firstLevel, int WTA_K, int scoreType, int patchSize, int fastThreshold)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.firstLevel
- The level of pyramid to put source image to. Previous layers are filled
with upscaled source image.WTA_K
- The number of points that produce each element of the oriented BRIEF descriptor. The
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).scoreType
- The default HARRIS_SCORE means that Harris algorithm is used to rank features
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.patchSize
- size of the patch used by the oriented BRIEF descriptor. Of course, on smaller
pyramid layers the perceived image area covered by a feature will be larger.fastThreshold
- the fast thresholdpublic static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold, int firstLevel, int WTA_K, int scoreType, int patchSize)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.firstLevel
- The level of pyramid to put source image to. Previous layers are filled
with upscaled source image.WTA_K
- The number of points that produce each element of the oriented BRIEF descriptor. The
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).scoreType
- The default HARRIS_SCORE means that Harris algorithm is used to rank features
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.patchSize
- size of the patch used by the oriented BRIEF descriptor. Of course, on smaller
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold, int firstLevel, int WTA_K, int scoreType)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.firstLevel
- The level of pyramid to put source image to. Previous layers are filled
with upscaled source image.WTA_K
- The number of points that produce each element of the oriented BRIEF descriptor. The
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).scoreType
- The default HARRIS_SCORE means that Harris algorithm is used to rank features
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold, int firstLevel, int WTA_K)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.firstLevel
- The level of pyramid to put source image to. Previous layers are filled
with upscaled source image.WTA_K
- The number of points that produce each element of the oriented BRIEF descriptor. The
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold, int firstLevel)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.firstLevel
- The level of pyramid to put source image to. Previous layers are filled
with upscaled source image.
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor, int nlevels, int edgeThreshold)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).edgeThreshold
- This is size of the border where the features are not detected. It should
roughly match the patchSize parameter.
with upscaled source image.
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor, int nlevels)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.nlevels
- The number of pyramid levels. The smallest level will have linear size equal to
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).
roughly match the patchSize parameter.
with upscaled source image.
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures, float scaleFactor)
nfeatures
- The maximum number of features to retain.scaleFactor
- Pyramid decimation ratio, greater than 1. scaleFactor==2 means the classical
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).
roughly match the patchSize parameter.
with upscaled source image.
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create(int nfeatures)
nfeatures
- The maximum number of features to retain.
pyramid, where each next level has 4x less pixels than the previous, but such a big scale factor
will degrade feature matching scores dramatically. On the other hand, too close to 1 scale factor
will mean that to cover certain scale range you will need more pyramid levels and so the speed
will suffer.
input_image_linear_size/pow(scaleFactor, nlevels - firstLevel).
roughly match the patchSize parameter.
with upscaled source image.
default value 2 means the BRIEF where we take a random point pair and compare their brightnesses,
so we get 0/1 response. Other possible values are 3 and 4. For example, 3 means that we take 3
random points (of course, those point coordinates are random, but they are generated from the
pre-defined seed, so each element of BRIEF descriptor is computed deterministically from the pixel
rectangle), find point of maximum brightness and output index of the winner (0, 1 or 2). Such
output will occupy 2 bits, and therefore it will need a special variant of Hamming distance,
denoted as NORM_HAMMING2 (2 bits per bin). When WTA_K=4, we take 4 random points to compute each
bin (that will also occupy 2 bits with possible values 0, 1, 2 or 3).
(the score is written to KeyPoint::score and is used to retain best nfeatures features);
FAST_SCORE is alternative value of the parameter that produces slightly less stable keypoints,
but it is a little faster to compute.
pyramid layers the perceived image area covered by a feature will be larger.public static ORB create()
public String getDefaultName()
Algorithm
getDefaultName
in class Feature2D
public double getScaleFactor()
public int getEdgeThreshold()
public int getFastThreshold()
public int getFirstLevel()
public int getMaxFeatures()
public int getNLevels()
public int getPatchSize()
public int getWTA_K()
public void setEdgeThreshold(int edgeThreshold)
public void setFastThreshold(int fastThreshold)
public void setFirstLevel(int firstLevel)
public void setMaxFeatures(int maxFeatures)
public void setNLevels(int nlevels)
public void setPatchSize(int patchSize)
public void setScaleFactor(double scaleFactor)
public void setScoreType(int scoreType)
public void setWTA_K(int wta_k)
Generated on Wed Oct 9 2019 23:24:43 UTC / OpenCV 4.1.2