Struct opencv::optflow::SparseRLOFOpticalFlow

pub struct SparseRLOFOpticalFlow { /* private fields */ }

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.

See also

optflow::calcOpticalFlowSparseRLOF(), optflow::RLOFOpticalFlowParameter

Implementations

impl SparseRLOFOpticalFlow

pub fn create( rlof_param: Ptr<RLOFOpticalFlowParameter>, forward_backward_threshold: f32 ) -> Result<Ptr<SparseRLOFOpticalFlow>>

Creates instance of SparseRLOFOpticalFlow

Parameters

• rlofParam: see setRLOFOpticalFlowParameter
• forwardBackwardThreshold: see setForwardBackward

C++ default parameters

• rlof_param: Ptr()
• forward_backward_threshold: 1.f

pub fn create_def() -> Result<Ptr<SparseRLOFOpticalFlow>>

Creates instance of SparseRLOFOpticalFlow

Parameters

• rlofParam: see setRLOFOpticalFlowParameter
• forwardBackwardThreshold: see setForwardBackward

Note

This alternative version of SparseRLOFOpticalFlow::create function uses the following default values for its arguments:

• rlof_param: Ptr()
• forward_backward_threshold: 1.f

Trait Implementations

impl AlgorithmTrait for SparseRLOFOpticalFlow

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

fn clear(&mut self) -> Result<()>

Clears the algorithm state

fn read(&mut self, fn_: &impl FileNodeTraitConst) -> Result<()>

Reads algorithm parameters from a file storage

impl AlgorithmTraitConst for SparseRLOFOpticalFlow

fn as_raw_Algorithm(&self) -> *const c_void

fn write(&self, fs: &mut impl FileStorageTrait) -> Result<()>

Stores algorithm parameters in a file storage

fn write_1(&self, fs: &mut impl FileStorageTrait, name: &str) -> Result<()>

Stores algorithm parameters in a file storage

fn write_with_name(&self, fs: &Ptr<FileStorage>, name: &str) -> Result<()>

@deprecated

fn write_with_name_def(&self, fs: &Ptr<FileStorage>) -> Result<()>

👎Deprecated:

Note

Deprecated: ## Note This alternative version of AlgorithmTraitConst::write_with_name function uses the following default values for its arguments:

fn empty(&self) -> Result<bool>

Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read

fn save(&self, filename: &str) -> Result<()>

Saves the algorithm to a file. In order to make this method work, the derived class must implement Algorithm::write(FileStorage& fs).

fn get_default_name(&self) -> Result<String>

Returns the algorithm string identifier. This string is used as top level xml/yml node tag when the object is saved to a file or string.

impl Boxed for SparseRLOFOpticalFlow

unsafe fn from_raw( ptr: <SparseRLOFOpticalFlow as OpenCVFromExtern>::ExternReceive ) -> Self

Wrap the specified raw pointer

fn into_raw( self ) -> <SparseRLOFOpticalFlow as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying raw pointer while consuming this wrapper.

fn as_raw( &self ) -> <SparseRLOFOpticalFlow as OpenCVTypeExternContainer>::ExternSend

Return the underlying raw pointer.

fn as_raw_mut( &mut self ) -> <SparseRLOFOpticalFlow as OpenCVTypeExternContainer>::ExternSendMut

Return the underlying mutable raw pointer

impl Debug for SparseRLOFOpticalFlow

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Drop for SparseRLOFOpticalFlow

fn drop(&mut self)

Executes the destructor for this type.

impl From<SparseRLOFOpticalFlow> for Algorithm

fn from(s: SparseRLOFOpticalFlow) -> Self

Converts to this type from the input type.

impl From<SparseRLOFOpticalFlow> for SparseOpticalFlow

fn from(s: SparseRLOFOpticalFlow) -> Self

Converts to this type from the input type.

impl SparseOpticalFlowTrait for SparseRLOFOpticalFlow

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

fn calc( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray, err: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

fn calc_def( &mut self, prev_img: &impl ToInputArray, next_img: &impl ToInputArray, prev_pts: &impl ToInputArray, next_pts: &mut impl ToInputOutputArray, status: &mut impl ToOutputArray ) -> Result<()>

Calculates a sparse optical flow.

impl SparseOpticalFlowTraitConst for SparseRLOFOpticalFlow

fn as_raw_SparseOpticalFlow(&self) -> *const c_void

impl SparseRLOFOpticalFlowTrait for SparseRLOFOpticalFlow

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

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

@copydoc DenseRLOFOpticalFlow::setRLOFOpticalFlowParameter

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

impl SparseRLOFOpticalFlowTraitConst for SparseRLOFOpticalFlow

fn as_raw_SparseRLOFOpticalFlow(&self) -> *const c_void

fn get_rlof_optical_flow_parameter( &self ) -> Result<Ptr<RLOFOpticalFlowParameter>>

@copydoc DenseRLOFOpticalFlow::setRLOFOpticalFlowParameter

fn get_forward_backward(&self) -> Result<f32>

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. * setForwardBackward

impl Send for SparseRLOFOpticalFlow