# opticalFlowLK

Object for estimating optical flow using Lucas-Kanade method

## Description

Create an optical flow object for estimating the direction and speed of a moving object using the Lucas-Kanade method. Use the object function estimateFlow to estimate the optical flow vectors. Using the reset object function, you can reset the internal state of the optical flow object.

## Creation

### Description

opticFlow = opticalFlowLK returns an optical flow object that you can use to estimate the direction and speed of the moving objects in a video. The optical flow is estimated using the Lucas-Kanade method.

example

opticFlow = opticalFlowLK('NoiseThreshold',threshold) returns an optical flow object with the property 'NoiseThreshold' specified as a Name,Value pair. Enclose the property name in quotes.

For example, opticalFlowLK('NoiseThreshold',0.05)

## Properties

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Threshold for noise reduction, specified as a positive scalar. As you increase this number, the movement of the objects has less impact on optical flow calculation.

## Object Functions

 estimateFlow Estimate optical flow reset Reset the internal state of the optical flow estimation object

## Examples

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Read a video file. Specify the timestamp of the frame to be read.

Create an optical flow object for estimating the optical flow using Lucas-Kanade method. Specify the threshold for noise reduction. The output is an optical flow object specifying the optical flow estimation method and its properties.

opticFlow = opticalFlowLK('NoiseThreshold',0.009);

Create a custom figure window to visualize the optical flow vectors.

h = figure;
movegui(h);
hViewPanel = uipanel(h,'Position',[0 0 1 1],'Title','Plot of Optical Flow Vectors');
hPlot = axes(hViewPanel);

Read the image frames and convert to grayscale images. Estimate the optical flow from consecutive image frames. Display the current image frame and plot the optical flow vectors as quiver plot.

frameGray = im2gray(frameRGB);
flow = estimateFlow(opticFlow,frameGray);
imshow(frameRGB)
hold on
plot(flow,'DecimationFactor',[5 5],'ScaleFactor',10,'Parent',hPlot);
hold off
pause(10^-3)
end

## Algorithms

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To compute the optical flow between two images, you must solve this optical flow constraint equation:

${I}_{x}u+{I}_{y}v+{I}_{t}=0$

.

• ${I}_{x}$, ${I}_{y}$, and ${I}_{t}$ are the spatiotemporal image brightness derivatives.

• u is the horizontal optical flow.

• v is the vertical optical flow.

## References

[1] Barron, J. L., D. J. Fleet, S. S. Beauchemin, and T. A. Burkitt. “ Performance of optical flow techniques.” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),236-242. Champaign, IL: CVPR, 1992.

## Version History

Introduced in R2015a