OpenCV
3.2.0
Open Source Computer Vision
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Classes | |
class | cv::BackgroundSubtractor |
Base class for background/foreground segmentation. : More... | |
class | cv::BackgroundSubtractorKNN |
K-nearest neigbours - based Background/Foreground Segmentation Algorithm. More... | |
class | cv::BackgroundSubtractorMOG2 |
Gaussian Mixture-based Background/Foreground Segmentation Algorithm. More... | |
Functions | |
Ptr< BackgroundSubtractorKNN > | cv::createBackgroundSubtractorKNN (int history=500, double dist2Threshold=400.0, bool detectShadows=true) |
Creates KNN Background Subtractor. More... | |
Ptr< BackgroundSubtractorMOG2 > | cv::createBackgroundSubtractorMOG2 (int history=500, double varThreshold=16, bool detectShadows=true) |
Creates MOG2 Background Subtractor. More... | |
Ptr<BackgroundSubtractorKNN> cv::createBackgroundSubtractorKNN | ( | int | history = 500 , |
double | dist2Threshold = 400.0 , |
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bool | detectShadows = true |
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Creates KNN Background Subtractor.
history | Length of the history. |
dist2Threshold | Threshold 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. |
detectShadows | If 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. |
Ptr<BackgroundSubtractorMOG2> cv::createBackgroundSubtractorMOG2 | ( | int | history = 500 , |
double | varThreshold = 16 , |
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bool | detectShadows = true |
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) |
Creates MOG2 Background Subtractor.
history | Length of the history. |
varThreshold | Threshold 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. |
detectShadows | If 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. |