Class used for calculation sparse optical flow and feature tracking with robust local optical flow (RLOF) algorithms.
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#include <opencv2/optflow/rlofflow.hpp>
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 [216] [217] [218] and [219] similar to the pyramidal iterative Lucas-Kanade method as proposed by [30]. More details and experiments can be found in the following thesis [220]. The implementation is derived from optflow::calcOpticalFlowPyrLK().
For the RLOF configuration see optflow::RLOFOpticalFlowParameter for further details. Parameters have been described in [216], [217], [218] and [219].
- Note
- SIMD parallelization is only available when compiling with SSE4.1.
- See also
- optflow::calcOpticalFlowSparseRLOF(), optflow::RLOFOpticalFlowParameter
◆ create()
Python: |
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| retval | = | cv.optflow.SparseRLOFOpticalFlow_create( | [, rlofParam[, forwardBackwardThreshold]] | ) |
Creates instance of SparseRLOFOpticalFlow.
- Parameters
-
rlofParam | see setRLOFOpticalFlowParameter |
forwardBackwardThreshold | see setForwardBackward |
◆ getForwardBackward()
virtual float cv::optflow::SparseRLOFOpticalFlow::getForwardBackward |
( |
| ) |
const |
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pure virtual |
Python: |
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| retval | = | cv.optflow_SparseRLOFOpticalFlow.getForwardBackward( | | ) |
◆ getRLOFOpticalFlowParameter()
Python: |
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| retval | = | cv.optflow_SparseRLOFOpticalFlow.getRLOFOpticalFlowParameter( | | ) |
◆ setForwardBackward()
virtual void cv::optflow::SparseRLOFOpticalFlow::setForwardBackward |
( |
float |
val | ) |
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pure virtual |
Python: |
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| None | = | cv.optflow_SparseRLOFOpticalFlow.setForwardBackward( | val | ) |
Threshold for the forward backward confidence check.
For each feature point a motion vector \( d_{I0,I1}(\mathbf{x}) \) is computed. If the forward backward error
\[ EP_{FB} = || d_{I0,I1} + d_{I1,I0} || \]
is larger than threshold given by this function then the status will not be used by the following vector field interpolation. \( d_{I1,I0} \) 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
◆ setRLOFOpticalFlowParameter()
Python: |
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| None | = | cv.optflow_SparseRLOFOpticalFlow.setRLOFOpticalFlowParameter( | val | ) |
The documentation for this class was generated from the following file: