| OpenCV 5.0.0alpha Open Source Computer Vision

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Classes | Namespaces | Functions
pcaflow.hpp File Reference

Implementation of the PCAFlow algorithm from the following paper: http://files.is.tue.mpg.de/black/papers/cvpr2015_pcaflow.pdf. More...

`#include "opencv2/core.hpp"`
`#include "opencv2/video.hpp"`
Include dependency graph for pcaflow.hpp:
This graph shows which files directly or indirectly include this file:

## Classes
class | cv::optflow::OpticalFlowPCAFlow
| PCAFlow algorithm. More...
class | cv::optflow::PCAPrior
| This class can be used for imposing a learned prior on the resulting optical flow. Solution will be regularized according to this prior. You need to generate appropriate prior file with "learn_prior.py" script beforehand. More...

## Namespaces
namespace | cv
namespace | cv::optflow

## Functions
Ptr< DenseOpticalFlow > | cv::optflow::createOptFlow_PCAFlow ()
| Creates an instance of PCAFlow.

## Detailed Description

Implementation of the PCAFlow algorithm from the following paper: http://files.is.tue.mpg.de/black/papers/cvpr2015_pcaflow.pdf.

Author
  Vladislav Samsonov vvlad.nosp@m.xx@g.nosp@m.mail..nosp@m.com

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There are some key differences which distinguish this algorithm from the original PCAFlow (see paper):

- Discrete Cosine Transform basis is used instead of basis extracted with PCA. Reasoning: DCT basis has comparable performance and it doesn't require additional storage space. Also, this decision helps to avoid overloading the algorithm with a lot of external input.
- Usage of built-in OpenCV feature tracking instead of libviso.