Trait opencv::optflow::SparseRLOFOpticalFlow

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pub trait SparseRLOFOpticalFlow: SparseRLOFOpticalFlowConst + SparseOpticalFlow {
    // Required method
    fn as_raw_mut_SparseRLOFOpticalFlow(&mut self) -> *mut c_void;

    // Provided methods
    fn set_rlof_optical_flow_parameter(
        &mut self,
        val: Ptr<RLOFOpticalFlowParameter>
    ) -> Result<()> { ... }
    fn set_forward_backward(&mut self, val: f32) -> Result<()> { ... }
}

Expand description

Class used for calculation sparse optical flow and feature tracking with robust local optical flow (RLOF) algorithms.

The RLOF is a fast local optical flow approach described in Senst2012 Senst2013 Senst2014 and Senst2016 similar to the pyramidal iterative Lucas-Kanade method as proposed by Bouguet00. More details and experiments can be found in the following thesis Senst2019. The implementation is derived from optflow::calcOpticalFlowPyrLK().

For the RLOF configuration see optflow::RLOFOpticalFlowParameter for further details. Parameters have been described in Senst2012, Senst2013, Senst2014 and Senst2016.

Note: SIMD parallelization is only available when compiling with SSE4.1.

Required Methods§

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fn as_raw_mut_SparseRLOFOpticalFlow(&mut self) -> *mut c_void

Provided Methods§

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fn set_rlof_optical_flow_parameter( &mut self, val: Ptr<RLOFOpticalFlowParameter> ) -> Result<()>

@copydoc DenseRLOFOpticalFlow::setRLOFOpticalFlowParameter

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fn set_forward_backward(&mut self, val: f32) -> Result<()>

Threshold for the forward backward confidence check For each feature point a motion vector $inline formula$ is computed. * If the forward backward error $block formula$ * is larger than threshold given by this function then the status will not be used by the following * vector field interpolation. $inline formula$ denotes the backward flow. Note, the forward backward test * will only be applied if the threshold > 0. This may results into a doubled runtime for the motion estimation. * see also: setForwardBackward