[−][src]Trait opencv::video::BackgroundSubtractorMOG2
Gaussian Mixture-based Background/Foreground Segmentation Algorithm.
The class implements the Gaussian mixture model background subtraction described in Zivkovic2004 and Zivkovic2006 .
Required methods
fn as_raw_BackgroundSubtractorMOG2(&self) -> *mut c_void
Provided methods
fn get_history(&self) -> Result<i32>
Returns the number of last frames that affect the background model
fn set_history(&mut self, history: i32) -> Result<()>
Sets the number of last frames that affect the background model
fn get_n_mixtures(&self) -> Result<i32>
Returns the number of gaussian components in the background model
fn set_n_mixtures(&mut self, nmixtures: i32) -> Result<()>
Sets the number of gaussian components in the background model.
The model needs to be reinitalized to reserve memory.
fn get_background_ratio(&self) -> Result<f64>
Returns the "background ratio" parameter of the algorithm
If a foreground pixel keeps semi-constant value for about backgroundRatio*history frames, it's considered background and added to the model as a center of a new component. It corresponds to TB parameter in the paper.
fn set_background_ratio(&mut self, ratio: f64) -> Result<()>
Sets the "background ratio" parameter of the algorithm
fn get_var_threshold(&self) -> Result<f64>
Returns the variance threshold for the pixel-model match
The main threshold on the squared Mahalanobis distance to decide if the sample is well described by the background model or not. Related to Cthr from the paper.
fn set_var_threshold(&mut self, var_threshold: f64) -> Result<()>
Sets the variance threshold for the pixel-model match
fn get_var_threshold_gen(&self) -> Result<f64>
Returns the variance threshold for the pixel-model match used for new mixture component generation
Threshold for the squared Mahalanobis distance that helps decide when a sample is close to the existing components (corresponds to Tg in the paper). If a pixel is not close to any component, it is considered foreground or added as a new component. 3 sigma => Tg=3*3=9 is default. A smaller Tg value generates more components. A higher Tg value may result in a small number of components but they can grow too large.
fn set_var_threshold_gen(&mut self, var_threshold_gen: f64) -> Result<()>
Sets the variance threshold for the pixel-model match used for new mixture component generation
fn get_var_init(&self) -> Result<f64>
Returns the initial variance of each gaussian component
fn set_var_init(&mut self, var_init: f64) -> Result<()>
Sets the initial variance of each gaussian component
fn get_var_min(&self) -> Result<f64>
fn set_var_min(&mut self, var_min: f64) -> Result<()>
fn get_var_max(&self) -> Result<f64>
fn set_var_max(&mut self, var_max: f64) -> Result<()>
fn get_complexity_reduction_threshold(&self) -> Result<f64>
Returns the complexity reduction threshold
This parameter defines the number of samples needed to accept to prove the component exists. CT=0.05 is a default value for all the samples. By setting CT=0 you get an algorithm very similar to the standard Stauffer&Grimson algorithm.
fn set_complexity_reduction_threshold(&mut self, ct: f64) -> Result<()>
Sets the complexity reduction threshold
fn get_detect_shadows(&self) -> Result<bool>
Returns the shadow detection flag
If true, the algorithm detects shadows and marks them. See createBackgroundSubtractorMOG2 for details.
fn set_detect_shadows(&mut self, detect_shadows: bool) -> Result<()>
Enables or disables shadow detection
fn get_shadow_value(&self) -> Result<i32>
Returns the shadow value
Shadow value is the value used to mark shadows in the foreground mask. Default value is 127. Value 0 in the mask always means background, 255 means foreground.
fn set_shadow_value(&mut self, value: i32) -> Result<()>
Sets the shadow value
fn get_shadow_threshold(&self) -> Result<f64>
Returns the shadow threshold
A shadow is detected if pixel is a darker version of the background. The shadow threshold (Tau in the paper) is a threshold defining how much darker the shadow can be. Tau= 0.5 means that if a pixel is more than twice darker then it is not shadow. See Prati, Mikic, Trivedi and Cucchiara, Detecting Moving Shadows..., IEEE PAMI,2003.
fn set_shadow_threshold(&mut self, threshold: f64) -> Result<()>
Sets the shadow threshold
fn apply(
&mut self,
image: &dyn ToInputArray,
fgmask: &mut dyn ToOutputArray,
learning_rate: f64
) -> Result<()>
&mut self,
image: &dyn ToInputArray,
fgmask: &mut dyn ToOutputArray,
learning_rate: f64
) -> Result<()>
Computes a foreground mask.
Parameters
- image: Next video frame. Floating point frame will be used without scaling and should be in range .
- 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.
C++ default parameters
- learning_rate: -1