Renesas / opencv-lib

Dependents:   RZ_A2M_Mbed_samples

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Motion Analysis

Data Structures

class  BackgroundSubtractor
 Base class for background/foreground segmentation. More...
class  BackgroundSubtractorMOG2
 Gaussian Mixture-based Background/Foreground Segmentation Algorithm. More...
class  BackgroundSubtractorKNN
 K-nearest neigbours - based Background/Foreground Segmentation Algorithm. More...

Functions

CV_EXPORTS_W Ptr
< BackgroundSubtractorMOG2 > 
createBackgroundSubtractorMOG2 (int history=500, double varThreshold=16, bool detectShadows=true)
 Creates MOG2 Background Subtractor.
CV_EXPORTS_W Ptr
< BackgroundSubtractorKNN > 
createBackgroundSubtractorKNN (int history=500, double dist2Threshold=400.0, bool detectShadows=true)
 Creates KNN Background Subtractor.

Function Documentation

CV_EXPORTS_W Ptr<BackgroundSubtractorKNN> cv::createBackgroundSubtractorKNN ( int  history = 500,
double  dist2Threshold = 400.0,
bool  detectShadows = true 
)

Creates KNN Background Subtractor.

Parameters:
historyLength of the history.
dist2ThresholdThreshold on the squared distance between the pixel and the sample to decide whether a pixel is close to that sample. This parameter does not affect the background update.
detectShadowsIf true, the algorithm will detect shadows and mark them. It decreases the speed a bit, so if you do not need this feature, set the parameter to false.
CV_EXPORTS_W Ptr<BackgroundSubtractorMOG2> cv::createBackgroundSubtractorMOG2 ( int  history = 500,
double  varThreshold = 16,
bool  detectShadows = true 
)

Creates MOG2 Background Subtractor.

Parameters:
historyLength of the history.
varThresholdThreshold on the squared Mahalanobis distance between the pixel and the model to decide whether a pixel is well described by the background model. This parameter does not affect the background update.
detectShadowsIf true, the algorithm will detect shadows and mark them. It decreases the speed a bit, so if you do not need this feature, set the parameter to false.