cv.OpticalFlowPCAFlow

PCAFlow algorithm

Implementation of the PCAFlow algorithm from the following paper: [Wulffcvpr2015].

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.

References

[Wulffcvpr2015]:

Jonas Wulff, Michael J. Black, "Efficient Sparse-to-Dense Optical Flow Estimation using a Learned Basis and Layers". PDF

	addlistener	Add listener for event.
	calc	Calculates an optical flow
	collectGarbage	Releases all inner buffers
	delete	Destructor
	eq	== (EQ) Test handle equality.
	findobj	Find objects matching specified conditions.
	findprop	Find property of MATLAB handle object.
	ge	>= (GE) Greater than or equal relation for handles.
	gt	> (GT) Greater than relation for handles.
Sealed	isvalid	Test handle validity.
	le	<= (LE) Less than or equal relation for handles.
	listener	Add listener for event without binding the listener to the source object.
	lt	< (LT) Less than relation for handles.
	ne	~= (NE) Not equal relation for handles.
	notify	Notify listeners of event.