Computes Dense Optical Flow between each pixel of two images using pyramidal Lucas-Kanade method.
Function
CuviStatus opticalFlowPyrLKDense(const CuviImage& previous,
const CuviImage& next,
Cuvi32f* flowX
Cuvi32f* flowY,
const CuviTrackingCriteria criteria,
const CuviStream& stream = CuviStream());
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Parameters
| Name
|
Type
|
Description
|
| previous
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CuviImage&
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The first image whose features are to be tracked
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| next
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CuviImage&
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Second image, in which to look for features of first image
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| flowX
|
Cuvi32f*
|
Horizontal optical flow
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| flowY
|
Cuvi32f*
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Vertical optical flow
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| criteria
|
const CuviFeaturesCriteria
|
A structure containing various parameters that affect optical flow calculation
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| stream
|
const CuviStream&
|
GPU stream ID for execution
|
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Image Type Support
| Input
|
Output
|
| 2x 8uC1
|
2x Cuvi32f*
|
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Samples
First Input Image (8-bit)
Second Input Image (8-bit)
Optical Flow Magnitude
Flow of selected points
Code Example
//Create two 8-bit Grays-scale CuviImage objects
CuviImage gimg1 = cuvi::io::loadImage(path,CUVI_LOAD_IMAGE_GRAYSCALE);
CuviImage gimg2 = cuvi::io::loadImage(path,CUVI_LOAD_IMAGE_GRAYSCALE);
Cuvi32f* flowX = new Cuvi32f[gimg1.width() * gimg1.height()];
Cuvi32f* flowY = new Cuvi32f[gimg1.width() * gimg1.height()];
//tracking criteria
CuviTrackingCriteria tc;
//Compute optical flow between first frame and second frame
cuvi::computerVision::opticalFlowPyrLKDense(gimg1,gimg2,flowX,flowY,tc);
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