pub trait CUDA_BackgroundSubtractorMOG: CUDA_BackgroundSubtractorMOGConst + BackgroundSubtractor {
    // Required method
    fn as_raw_mut_CUDA_BackgroundSubtractorMOG(&mut self) -> *mut c_void;

    // Provided methods
    fn apply(
        &mut self,
        image: &dyn ToInputArray,
        fgmask: &mut dyn ToOutputArray,
        learning_rate: f64,
        stream: &mut Stream
    ) -> Result<()> { ... }
    fn get_background_image_1(
        &mut self,
        background_image: &mut GpuMat,
        stream: &mut Stream
    ) -> Result<()> { ... }
    fn set_history(&mut self, nframes: i32) -> Result<()> { ... }
    fn set_n_mixtures(&mut self, nmix: i32) -> Result<()> { ... }
    fn set_background_ratio(&mut self, background_ratio: f64) -> Result<()> { ... }
    fn set_noise_sigma(&mut self, noise_sigma: f64) -> Result<()> { ... }
}
Expand description

Gaussian Mixture-based Background/Foreground Segmentation Algorithm.

The class discriminates between foreground and background pixels by building and maintaining a model of the background. Any pixel which does not fit this model is then deemed to be foreground. The class implements algorithm described in MOG2001 .

See also

BackgroundSubtractorMOG

Note:

  • An example on gaussian mixture based background/foreground segmantation can be found at opencv_source_code/samples/gpu/bgfg_segm.cpp

Required Methods§

Provided Methods§

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fn apply( &mut self, image: &dyn ToInputArray, fgmask: &mut dyn ToOutputArray, learning_rate: f64, stream: &mut Stream ) -> Result<()>

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fn get_background_image_1( &mut self, background_image: &mut GpuMat, stream: &mut Stream ) -> Result<()>

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fn set_history(&mut self, nframes: i32) -> Result<()>

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fn set_n_mixtures(&mut self, nmix: i32) -> Result<()>

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fn set_background_ratio(&mut self, background_ratio: f64) -> Result<()>

source

fn set_noise_sigma(&mut self, noise_sigma: f64) -> Result<()>

Implementors§