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

[305]

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.