Trait CUDA_OpticalFlowDual_TVL1TraitConst

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pub trait CUDA_OpticalFlowDual_TVL1TraitConst: CUDA_DenseOpticalFlowTraitConst {
    // Required method
    fn as_raw_CUDA_OpticalFlowDual_TVL1(&self) -> *const c_void;

    // Provided methods
    fn get_tau(&self) -> Result<f64> { ... }
    fn get_lambda(&self) -> Result<f64> { ... }
    fn get_gamma(&self) -> Result<f64> { ... }
    fn get_theta(&self) -> Result<f64> { ... }
    fn get_num_scales(&self) -> Result<i32> { ... }
    fn get_num_warps(&self) -> Result<i32> { ... }
    fn get_epsilon(&self) -> Result<f64> { ... }
    fn get_num_iterations(&self) -> Result<i32> { ... }
    fn get_scale_step(&self) -> Result<f64> { ... }
    fn get_use_initial_flow(&self) -> Result<bool> { ... }
}

Expand description

Constant methods for crate::cudaoptflow::CUDA_OpticalFlowDual_TVL1

Required Methods§

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fn as_raw_CUDA_OpticalFlowDual_TVL1(&self) -> *const c_void

Provided Methods§

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fn get_tau(&self) -> Result<f64>

Time step of the numerical scheme.

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fn get_lambda(&self) -> Result<f64>

Weight parameter for the data term, attachment parameter. This is the most relevant parameter, which determines the smoothness of the output. The smaller this parameter is, the smoother the solutions we obtain. It depends on the range of motions of the images, so its value should be adapted to each image sequence.

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fn get_gamma(&self) -> Result<f64>

Weight parameter for (u - v)^2, tightness parameter. It serves as a link between the attachment and the regularization terms. In theory, it should have a small value in order to maintain both parts in correspondence. The method is stable for a large range of values of this parameter.

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fn get_theta(&self) -> Result<f64>

parameter used for motion estimation. It adds a variable allowing for illumination variations Set this parameter to 1. if you have varying illumination. See: Chambolle et al, A First-Order Primal-Dual Algorithm for Convex Problems with Applications to Imaging Journal of Mathematical imaging and vision, may 2011 Vol 40 issue 1, pp 120-145

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fn get_num_scales(&self) -> Result<i32>

Number of scales used to create the pyramid of images.

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fn get_num_warps(&self) -> Result<i32>

Number of warpings per scale. Represents the number of times that I1(x+u0) and grad( I1(x+u0) ) are computed per scale. This is a parameter that assures the stability of the method. It also affects the running time, so it is a compromise between speed and accuracy.

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fn get_epsilon(&self) -> Result<f64>

Stopping criterion threshold used in the numerical scheme, which is a trade-off between precision and running time. A small value will yield more accurate solutions at the expense of a slower convergence.

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