View Source Evision.BgSegm (Evision v0.1.38)
Summary
Functions
Creates a CNT Background Subtractor
Creates a CNT Background Subtractor
Creates a GMG Background Subtractor
Creates a GMG Background Subtractor
Creates an instance of BackgroundSubtractorGSOC algorithm.
Creates an instance of BackgroundSubtractorGSOC algorithm.
Creates an instance of BackgroundSubtractorLSBP algorithm.
Creates an instance of BackgroundSubtractorLSBP algorithm.
Creates mixture-of-gaussian background subtractor
Creates mixture-of-gaussian background subtractor
Creates an instance of SyntheticSequenceGenerator.
Creates an instance of SyntheticSequenceGenerator.
Types
@type t() :: %Evision.BgSegm{ref: reference()}
Type that represents an BgSegm struct.
ref.
reference()The underlying erlang resource variable.
Functions
@spec createBackgroundSubtractorCNT() :: Evision.BgSegm.BackgroundSubtractorCNT.t() | {:error, String.t()}
Creates a CNT Background Subtractor
Keyword Arguments
minPixelStability:
int.number of frames with same pixel color to consider stable
useHistory:
bool.determines if we're giving a pixel credit for being stable for a long time
maxPixelStability:
int.maximum allowed credit for a pixel in history
isParallel:
bool.determines if we're parallelizing the algorithm
Return
- retval:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Python prototype (for reference only):
createBackgroundSubtractorCNT([, minPixelStability[, useHistory[, maxPixelStability[, isParallel]]]]) -> retval@spec createBackgroundSubtractorCNT([{atom(), term()}, ...] | nil) :: Evision.BgSegm.BackgroundSubtractorCNT.t() | {:error, String.t()}
Creates a CNT Background Subtractor
Keyword Arguments
minPixelStability:
int.number of frames with same pixel color to consider stable
useHistory:
bool.determines if we're giving a pixel credit for being stable for a long time
maxPixelStability:
int.maximum allowed credit for a pixel in history
isParallel:
bool.determines if we're parallelizing the algorithm
Return
- retval:
Evision.BgSegm.BackgroundSubtractorCNT.t()
Python prototype (for reference only):
createBackgroundSubtractorCNT([, minPixelStability[, useHistory[, maxPixelStability[, isParallel]]]]) -> retval@spec createBackgroundSubtractorGMG() :: Evision.BgSegm.BackgroundSubtractorGMG.t() | {:error, String.t()}
Creates a GMG Background Subtractor
Keyword Arguments
initializationFrames:
int.number of frames used to initialize the background models.
decisionThreshold:
double.Threshold value, above which it is marked foreground, else background.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorGMG.t()
Python prototype (for reference only):
createBackgroundSubtractorGMG([, initializationFrames[, decisionThreshold]]) -> retval@spec createBackgroundSubtractorGMG([{atom(), term()}, ...] | nil) :: Evision.BgSegm.BackgroundSubtractorGMG.t() | {:error, String.t()}
Creates a GMG Background Subtractor
Keyword Arguments
initializationFrames:
int.number of frames used to initialize the background models.
decisionThreshold:
double.Threshold value, above which it is marked foreground, else background.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorGMG.t()
Python prototype (for reference only):
createBackgroundSubtractorGMG([, initializationFrames[, decisionThreshold]]) -> retval@spec createBackgroundSubtractorGSOC() :: Evision.BgSegm.BackgroundSubtractorGSOC.t() | {:error, String.t()}
Creates an instance of BackgroundSubtractorGSOC algorithm.
Keyword Arguments
mc:
int.Whether to use camera motion compensation.
nSamples:
int.Number of samples to maintain at each point of the frame.
replaceRate:
float.Probability of replacing the old sample - how fast the model will update itself.
propagationRate:
float.Probability of propagating to neighbors.
hitsThreshold:
int.How many positives the sample must get before it will be considered as a possible replacement.
alpha:
float.Scale coefficient for threshold.
beta:
float.Bias coefficient for threshold.
blinkingSupressionDecay:
float.Blinking supression decay factor.
blinkingSupressionMultiplier:
float.Blinking supression multiplier.
noiseRemovalThresholdFacBG:
float.Strength of the noise removal for background points.
noiseRemovalThresholdFacFG:
float.Strength of the noise removal for foreground points.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorGSOC.t()
Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.
Python prototype (for reference only):
createBackgroundSubtractorGSOC([, mc[, nSamples[, replaceRate[, propagationRate[, hitsThreshold[, alpha[, beta[, blinkingSupressionDecay[, blinkingSupressionMultiplier[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG]]]]]]]]]]]) -> retval@spec createBackgroundSubtractorGSOC([{atom(), term()}, ...] | nil) :: Evision.BgSegm.BackgroundSubtractorGSOC.t() | {:error, String.t()}
Creates an instance of BackgroundSubtractorGSOC algorithm.
Keyword Arguments
mc:
int.Whether to use camera motion compensation.
nSamples:
int.Number of samples to maintain at each point of the frame.
replaceRate:
float.Probability of replacing the old sample - how fast the model will update itself.
propagationRate:
float.Probability of propagating to neighbors.
hitsThreshold:
int.How many positives the sample must get before it will be considered as a possible replacement.
alpha:
float.Scale coefficient for threshold.
beta:
float.Bias coefficient for threshold.
blinkingSupressionDecay:
float.Blinking supression decay factor.
blinkingSupressionMultiplier:
float.Blinking supression multiplier.
noiseRemovalThresholdFacBG:
float.Strength of the noise removal for background points.
noiseRemovalThresholdFacFG:
float.Strength of the noise removal for foreground points.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorGSOC.t()
Implementation of the different yet better algorithm which is called GSOC, as it was implemented during GSOC and was not originated from any paper.
Python prototype (for reference only):
createBackgroundSubtractorGSOC([, mc[, nSamples[, replaceRate[, propagationRate[, hitsThreshold[, alpha[, beta[, blinkingSupressionDecay[, blinkingSupressionMultiplier[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG]]]]]]]]]]]) -> retval@spec createBackgroundSubtractorLSBP() :: Evision.BgSegm.BackgroundSubtractorLSBP.t() | {:error, String.t()}
Creates an instance of BackgroundSubtractorLSBP algorithm.
Keyword Arguments
mc:
int.Whether to use camera motion compensation.
nSamples:
int.Number of samples to maintain at each point of the frame.
lSBPRadius:
int.LSBP descriptor radius.
tlower:
float.Lower bound for T-values. See @cite LGuo2016 for details.
tupper:
float.Upper bound for T-values. See @cite LGuo2016 for details.
tinc:
float.Increase step for T-values. See @cite LGuo2016 for details.
tdec:
float.Decrease step for T-values. See @cite LGuo2016 for details.
rscale:
float.Scale coefficient for threshold values.
rincdec:
float.Increase/Decrease step for threshold values.
noiseRemovalThresholdFacBG:
float.Strength of the noise removal for background points.
noiseRemovalThresholdFacFG:
float.Strength of the noise removal for foreground points.
lSBPthreshold:
int.Threshold for LSBP binary string.
minCount:
int.Minimal number of matches for sample to be considered as foreground.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorLSBP.t()
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at @cite LGuo2016
Python prototype (for reference only):
createBackgroundSubtractorLSBP([, mc[, nSamples[, LSBPRadius[, Tlower[, Tupper[, Tinc[, Tdec[, Rscale[, Rincdec[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG[, LSBPthreshold[, minCount]]]]]]]]]]]]]) -> retval@spec createBackgroundSubtractorLSBP([{atom(), term()}, ...] | nil) :: Evision.BgSegm.BackgroundSubtractorLSBP.t() | {:error, String.t()}
Creates an instance of BackgroundSubtractorLSBP algorithm.
Keyword Arguments
mc:
int.Whether to use camera motion compensation.
nSamples:
int.Number of samples to maintain at each point of the frame.
lSBPRadius:
int.LSBP descriptor radius.
tlower:
float.Lower bound for T-values. See @cite LGuo2016 for details.
tupper:
float.Upper bound for T-values. See @cite LGuo2016 for details.
tinc:
float.Increase step for T-values. See @cite LGuo2016 for details.
tdec:
float.Decrease step for T-values. See @cite LGuo2016 for details.
rscale:
float.Scale coefficient for threshold values.
rincdec:
float.Increase/Decrease step for threshold values.
noiseRemovalThresholdFacBG:
float.Strength of the noise removal for background points.
noiseRemovalThresholdFacFG:
float.Strength of the noise removal for foreground points.
lSBPthreshold:
int.Threshold for LSBP binary string.
minCount:
int.Minimal number of matches for sample to be considered as foreground.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorLSBP.t()
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at @cite LGuo2016
Python prototype (for reference only):
createBackgroundSubtractorLSBP([, mc[, nSamples[, LSBPRadius[, Tlower[, Tupper[, Tinc[, Tdec[, Rscale[, Rincdec[, noiseRemovalThresholdFacBG[, noiseRemovalThresholdFacFG[, LSBPthreshold[, minCount]]]]]]]]]]]]]) -> retval@spec createBackgroundSubtractorMOG() :: Evision.BgSegm.BackgroundSubtractorMOG.t() | {:error, String.t()}
Creates mixture-of-gaussian background subtractor
Keyword Arguments
history:
int.Length of the history.
nmixtures:
int.Number of Gaussian mixtures.
backgroundRatio:
double.Background ratio.
noiseSigma:
double.Noise strength (standard deviation of the brightness or each color channel). 0 means some automatic value.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Python prototype (for reference only):
createBackgroundSubtractorMOG([, history[, nmixtures[, backgroundRatio[, noiseSigma]]]]) -> retval@spec createBackgroundSubtractorMOG([{atom(), term()}, ...] | nil) :: Evision.BgSegm.BackgroundSubtractorMOG.t() | {:error, String.t()}
Creates mixture-of-gaussian background subtractor
Keyword Arguments
history:
int.Length of the history.
nmixtures:
int.Number of Gaussian mixtures.
backgroundRatio:
double.Background ratio.
noiseSigma:
double.Noise strength (standard deviation of the brightness or each color channel). 0 means some automatic value.
Return
- retval:
Evision.BgSegm.BackgroundSubtractorMOG.t()
Python prototype (for reference only):
createBackgroundSubtractorMOG([, history[, nmixtures[, backgroundRatio[, noiseSigma]]]]) -> retval@spec createSyntheticSequenceGenerator( Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in() ) :: Evision.BgSegm.SyntheticSequenceGenerator.t() | {:error, String.t()}
Creates an instance of SyntheticSequenceGenerator.
Positional Arguments
background:
Evision.Mat.t().Background image for object.
object:
Evision.Mat.t().Object image which will move slowly over the background.
Keyword Arguments
amplitude:
double.Amplitude of wave distortion applied to background.
wavelength:
double.Length of waves in distortion applied to background.
wavespeed:
double.How fast waves will move.
objspeed:
double.How fast object will fly over background.
Return
- retval:
Evision.BgSegm.SyntheticSequenceGenerator.t()
Python prototype (for reference only):
createSyntheticSequenceGenerator(background, object[, amplitude[, wavelength[, wavespeed[, objspeed]]]]) -> retval@spec createSyntheticSequenceGenerator( Evision.Mat.maybe_mat_in(), Evision.Mat.maybe_mat_in(), [{atom(), term()}, ...] | nil ) :: Evision.BgSegm.SyntheticSequenceGenerator.t() | {:error, String.t()}
Creates an instance of SyntheticSequenceGenerator.
Positional Arguments
background:
Evision.Mat.t().Background image for object.
object:
Evision.Mat.t().Object image which will move slowly over the background.
Keyword Arguments
amplitude:
double.Amplitude of wave distortion applied to background.
wavelength:
double.Length of waves in distortion applied to background.
wavespeed:
double.How fast waves will move.
objspeed:
double.How fast object will fly over background.
Return
- retval:
Evision.BgSegm.SyntheticSequenceGenerator.t()
Python prototype (for reference only):
createSyntheticSequenceGenerator(background, object[, amplitude[, wavelength[, wavespeed[, objspeed]]]]) -> retval