Class cv::bgsegm::BackgroundSubtractorLSBP#
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [128].
#include <opencv2/bgsegm.hpp>Collaboration diagram for cv::bgsegm::BackgroundSubtractorLSBP:
Public Member Functions#
Public Member Functions inherited from cv::BackgroundSubtractor
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Computes a foreground mask with known foreground mask input. |
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Computes a foreground mask. |
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Computes a background image. |
Public Member Functions inherited from cv::Algorithm
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Clears the algorithm state. |
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Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. |
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Reads algorithm parameters from a file storage. |
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Stores algorithm parameters in a file storage. |
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Static Public Member Functions#
Static Public Member Functions inherited from cv::Algorithm
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Loads algorithm from the file. |
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Loads algorithm from a String. |
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Reads algorithm from the file node. |
Additional Inherited Members#
Protected Member Functions inherited from cv::Algorithm
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Detailed Description#
Background Subtraction using Local SVD Binary Pattern. More details about the algorithm can be found at [128].
Member Function Documentation#
apply()#
void cv::bgsegm::BackgroundSubtractorLSBP::apply(
InputArray image,
InputArray knownForegroundMask,
OutputArray fgmask,
double learningRate = -1 )
Computes a foreground mask with known foreground mask input.
Note
This method has a default virtual implementation that throws a “not impemented” error. Foreground masking may not be supported by all background subtractors.
Parameters
image— Next video frame. Floating point frame will be used without scaling and should be in range \([0,255]\).fgmask— The output foreground mask as an 8-bit binary image.knownForegroundMask— The mask for inputting already known foreground, allows model to ignore pixels.learningRate— The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
apply()#
void cv::bgsegm::BackgroundSubtractorLSBP::apply(
InputArray image,
OutputArray fgmask,
double learningRate = -1 )
Computes a foreground mask.
Parameters
image— Next video frame.fgmask— The output foreground mask as an 8-bit binary image.learningRate— The value between 0 and 1 that indicates how fast the background model is learnt. Negative parameter value makes the algorithm to use some automatically chosen learning rate. 0 means that the background model is not updated at all, 1 means that the background model is completely reinitialized from the last frame.
getBackgroundImage()#
void cv::bgsegm::BackgroundSubtractorLSBP::getBackgroundImage(OutputArray backgroundImage)
Computes a background image.
Note
Sometimes the background image can be very blurry, as it contain the average background statistics.
Parameters
backgroundImage— The output background image.
Source file#
The documentation for this class was generated from the following file:
opencv2/bgsegm.hpp