OpenCV  4.5.1
Open Source Computer Vision
Classes | Functions
Motion Analysis

Classes

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

Functions

Ptr< BackgroundSubtractorKNNcv::createBackgroundSubtractorKNN (int history=500, double dist2Threshold=400.0, bool detectShadows=true)
 Creates KNN Background Subtractor. More...
 
Ptr< BackgroundSubtractorMOG2cv::createBackgroundSubtractorMOG2 (int history=500, double varThreshold=16, bool detectShadows=true)
 Creates MOG2 Background Subtractor. More...
 

Detailed Description

Function Documentation

◆ createBackgroundSubtractorKNN()

Ptr<BackgroundSubtractorKNN> cv::createBackgroundSubtractorKNN ( int  history = 500,
double  dist2Threshold = 400.0,
bool  detectShadows = true 
)
Python:
retval=cv.createBackgroundSubtractorKNN([, history[, dist2Threshold[, detectShadows]]])

#include <opencv2/video/background_segm.hpp>

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.

◆ createBackgroundSubtractorMOG2()

Ptr<BackgroundSubtractorMOG2> cv::createBackgroundSubtractorMOG2 ( int  history = 500,
double  varThreshold = 16,
bool  detectShadows = true 
)
Python:
retval=cv.createBackgroundSubtractorMOG2([, history[, varThreshold[, detectShadows]]])

#include <opencv2/video/background_segm.hpp>

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.
Examples:
samples/cpp/segment_objects.cpp.