改进的背景 前景分割方法


class cv::bgsegm::BackgroundSubtractorCNT
Background subtraction based on counting. 更多...
class cv::bgsegm::BackgroundSubtractorGMG
Background Subtractor module based on the algorithm given in [84] . 更多...
class cv::bgsegm::BackgroundSubtractorGSOC
Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper. 更多...
class cv::bgsegm::BackgroundSubtractorLSBP
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [92] . 更多...
class cv::bgsegm::BackgroundSubtractorLSBPDesc
This is for calculation of the LSBP descriptors. 更多...
class cv::bgsegm::BackgroundSubtractorMOG
Gaussian Mixture-based Background/Foreground Segmentation Algorithm . 更多...
class cv::bgsegm::SyntheticSequenceGenerator
Synthetic frame sequence generator for testing background subtraction algorithms. 更多...

枚举

enum cv::bgsegm::LSBPCameraMotionCompensation {
cv::bgsegm::LSBP_CAMERA_MOTION_COMPENSATION_NONE = 0,
cv::bgsegm::LSBP_CAMERA_MOTION_COMPENSATION_LK
}

函数

Ptr < BackgroundSubtractorCNT > cv::bgsegm::createBackgroundSubtractorCNT (int minPixelStability=15, bool useHistory=true, int maxPixelStability=15 *60, bool isParallel=true)
Creates a CNT Background Subtractor. 更多...
Ptr < BackgroundSubtractorGMG > cv::bgsegm::createBackgroundSubtractorGMG (int initializationFrames=120, double decisionThreshold=0.8)
Creates a GMG Background Subtractor. 更多...
Ptr < BackgroundSubtractorGSOC > cv::bgsegm::createBackgroundSubtractorGSOC (int mc= LSBP_CAMERA_MOTION_COMPENSATION_NONE , int nSamples=20, float replaceRate=0.003f, float propagationRate=0.01f, int hitsThreshold=32, float alpha=0.01f, float beta=0.0022f, float blinkingSupressionDecay=0.1f, float blinkingSupressionMultiplier=0.1f, float noiseRemovalThresholdFacBG=0.0004f, float noiseRemovalThresholdFacFG=0.0008f)
Creates an instance of BackgroundSubtractorGSOC algorithm. 更多...
Ptr < BackgroundSubtractorLSBP > cv::bgsegm::createBackgroundSubtractorLSBP (int mc= LSBP_CAMERA_MOTION_COMPENSATION_NONE , int nSamples=20, int LSBPRadius=16, float Tlower=2.0f, float Tupper=32.0f, float Tinc=1.0f, float Tdec=0.05f, float Rscale=10.0f, float Rincdec=0.005f, float noiseRemovalThresholdFacBG=0.0004f, float noiseRemovalThresholdFacFG=0.0008f, int LSBPthreshold=8, int minCount=2)
Creates an instance of BackgroundSubtractorLSBP algorithm. 更多...
Ptr < BackgroundSubtractorMOG > cv::bgsegm::createBackgroundSubtractorMOG (int history=200, int nmixtures=5, double backgroundRatio=0.7, double noiseSigma=0)
Creates mixture-of-gaussian background subtractor. 更多...
Ptr < SyntheticSequenceGenerator > cv::bgsegm::createSyntheticSequenceGenerator ( InputArray background, InputArray object, double amplitude=2.0, double wavelength=20.0, double wavespeed=0.2, double objspeed=6.0)
Creates an instance of SyntheticSequenceGenerator . 更多...

详细描述

枚举类型文档编制

LSBPCameraMotionCompensation

#include < opencv2/bgsegm.hpp >

枚举器
LSBP_CAMERA_MOTION_COMPENSATION_NONE
Python: cv.bgsegm.LSBP_CAMERA_MOTION_COMPENSATION_NONE
LSBP_CAMERA_MOTION_COMPENSATION_LK
Python: cv.bgsegm.LSBP_CAMERA_MOTION_COMPENSATION_LK

函数文档编制

createBackgroundSubtractorCNT()

Ptr < BackgroundSubtractorCNT > cv::bgsegm::createBackgroundSubtractorCNT ( int minPixelStability = 15 ,
bool useHistory = true ,
int maxPixelStability = 15 *60 ,
bool isParallel = true
)
Python:
retval = cv.bgsegm.createBackgroundSubtractorCNT( [, minPixelStability[, useHistory[, maxPixelStability[, isParallel]]]] )

#include < opencv2/bgsegm.hpp >

Creates a CNT Background Subtractor.

Parameters
minPixelStability number of frames with same pixel color to consider stable
useHistory determines if we're giving a pixel credit for being stable for a long time
maxPixelStability maximum allowed credit for a pixel in history
isParallel determines if we're parallelizing the algorithm

createBackgroundSubtractorGMG()

Ptr < BackgroundSubtractorGMG > cv::bgsegm::createBackgroundSubtractorGMG ( int initializationFrames = 120 ,
double decisionThreshold = 0.8
)
Python:
retval = cv.bgsegm.createBackgroundSubtractorGMG( [, initializationFrames[, decisionThreshold]] )

#include < opencv2/bgsegm.hpp >

Creates a GMG Background Subtractor.

Parameters
initializationFrames number of frames used to initialize the background models.
decisionThreshold Threshold value, above which it is marked foreground, else background.

createBackgroundSubtractorGSOC()

Ptr < BackgroundSubtractorGSOC > cv::bgsegm::createBackgroundSubtractorGSOC ( int mc = LSBP_CAMERA_MOTION_COMPENSATION_NONE ,
int nSamples = 20 ,
float replaceRate = 0.003f ,
float propagationRate = 0.01f ,
int hitsThreshold = 32 ,
float alpha = 0.01f ,
float beta = 0.0022f ,
float blinkingSupressionDecay = 0.1f ,
float blinkingSupressionMultiplier = 0.1f ,
float noiseRemovalThresholdFacBG = 0.0004f ,
float noiseRemovalThresholdFacFG = 0.0008f
)
Python:
retval = cv.bgsegm.createBackgroundSubtractorGSOC( [, mc[, nSamples[, replaceRate[, propagationRate[, hitsThreshold[, alpha[, beta[, blinkingSupressionDecay[, blinkingSupressionMultiplier[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG]]]]]]]]]]] )

#include < opencv2/bgsegm.hpp >

Creates an instance of BackgroundSubtractorGSOC algorithm.

Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.

Parameters
mc Whether to use camera motion compensation.
nSamples Number of samples to maintain at each point of the frame.
replaceRate Probability of replacing the old sample - how fast the model will update itself.
propagationRate Probability of propagating to neighbors.
hitsThreshold How many positives the sample must get before it will be considered as a possible replacement.
alpha Scale coefficient for threshold.
beta Bias coefficient for threshold.
blinkingSupressionDecay Blinking supression decay factor.
blinkingSupressionMultiplier Blinking supression multiplier.
noiseRemovalThresholdFacBG Strength of the noise removal for background points.
noiseRemovalThresholdFacFG Strength of the noise removal for foreground points.

createBackgroundSubtractorLSBP()

Ptr < BackgroundSubtractorLSBP > cv::bgsegm::createBackgroundSubtractorLSBP ( int mc = LSBP_CAMERA_MOTION_COMPENSATION_NONE ,
int nSamples = 20 ,
int LSBPRadius = 16 ,
float Tlower = 2.0f ,
float Tupper = 32.0f ,
float Tinc = 1.0f ,
float Tdec = 0.05f ,
float Rscale = 10.0f ,
float Rincdec = 0.005f ,
float noiseRemovalThresholdFacBG = 0.0004f ,
float noiseRemovalThresholdFacFG = 0.0008f ,
int LSBPthreshold = 8 ,
int minCount = 2
)
Python:
retval = cv.bgsegm.createBackgroundSubtractorLSBP( [, mc[, nSamples[, LSBPRadius[, Tlower[, Tupper[, Tinc[, Tdec[, Rscale[, Rincdec[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG[, LSBPthreshold[, minCount]]]]]]]]]]]]] )

#include < opencv2/bgsegm.hpp >

Creates an instance of BackgroundSubtractorLSBP algorithm.

Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [92]

Parameters
mc Whether to use camera motion compensation.
nSamples Number of samples to maintain at each point of the frame.
LSBPRadius LSBP descriptor radius.
Tlower Lower bound for T-values. See [92] for details.
Tupper Upper bound for T-values. See [92] for details.
Tinc Increase step for T-values. See [92] for details.
Tdec Decrease step for T-values. See [92] for details.
Rscale Scale coefficient for threshold values.
Rincdec Increase/Decrease step for threshold values.
noiseRemovalThresholdFacBG Strength of the noise removal for background points.
noiseRemovalThresholdFacFG Strength of the noise removal for foreground points.
LSBPthreshold Threshold for LSBP binary string.
minCount Minimal number of matches for sample to be considered as foreground.

createBackgroundSubtractorMOG()

Ptr < BackgroundSubtractorMOG > cv::bgsegm::createBackgroundSubtractorMOG ( int history = 200 ,
int nmixtures = 5 ,
double backgroundRatio = 0.7 ,
double noiseSigma = 0
)
Python:
retval = cv.bgsegm.createBackgroundSubtractorMOG( [, history[, nmixtures[, backgroundRatio[, noiseSigma]]]] )

#include < opencv2/bgsegm.hpp >

Creates mixture-of-gaussian background subtractor.

Parameters
history Length of the history.
nmixtures Number of Gaussian mixtures.
backgroundRatio Background ratio.
noiseSigma Noise strength (standard deviation of the brightness or each color channel). 0 means some automatic value.

createSyntheticSequenceGenerator()

Ptr < SyntheticSequenceGenerator > cv::bgsegm::createSyntheticSequenceGenerator ( InputArray background ,
InputArray object ,
double amplitude = 2.0 ,
double wavelength = 20.0 ,
double wavespeed = 0.2 ,
double objspeed = 6.0
)
Python:
retval = cv.bgsegm.createSyntheticSequenceGenerator( background, object[, amplitude[, wavelength[, wavespeed[, objspeed]]]] )

#include < opencv2/bgsegm.hpp >

Creates an instance of SyntheticSequenceGenerator .

Parameters
background Background image for object.
object Object image which will move slowly over the background.
amplitude Amplitude of wave distortion applied to background.
wavelength Length of waves in distortion applied to background.
wavespeed How fast waves will move.
objspeed How fast object will fly over background.