Optical flow between two frames
5 次查看(过去 30 天)
显示 更早的评论
I have used the following code to estimate a velocity of a moving box, u and v values of different points at the same block are not close. How can I estimate the representive u & v values?
obj = VideoReader('bigbox.mp4');
for k = 1 : 2
this_frame = readFrame(obj);
thisfig = figure();
thisax = axes('Parent', thisfig);
image(this_frame, 'Parent', thisax);
title(thisax, sprintf('Frame #%d', k));
end
%% optical flow
I1=imread('Framep#1.png');
I2=imread('Framep#2.png');
modelname = 'ex_blkopticalflow.slx';
open_system(modelname)
out = sim(modelname);
Vx = real(out.simout);
Vy = imag(out.simout);
img = out.simout1;
flow = opticalFlow(Vx,Vy);
figure
imshow(img)
hold on
plot(flow,'DecimationFactor',[5 5],'ScaleFactor',40);
1 个评论
Image Analyst
2023-9-16
If you have any more questions, then attach your data ('bigbox.mp4') with the paperclip icon after you read this:
回答(1 个)
Ishaan
2025-3-26
Hey,
I understand that you are getting a wide range of horizontal (Vx or u) and vertical (Vy or v) velocities at different points on the same block, and you want to get a representative value, a single value that best describes the velocity of a block.
The following are some approaches you can consider to aggregate the “opticalFlow” vectors into a single and meaningful value.
Note: divide the optical flow field into non-overlapping blocks before applying these methods
1. Block Average
Compute the mean “u” and “v” for each block and take it as representative value
2. Median Filtering (suggested)
Using median makes the aggregation robust to outliers, as it avoids the influence of noise / extreme values.
3. Mode
Compute the most common value of u and v to represent dominant motion in each block.
4. Weighted Average
While computing the mean value, give more importance to velocities with higher magnitude. This would aid if the noise has lower magnitude than the actual motion.
5. Principal Component Analysis
This method will identify the dominant motion in each block and gives a compact representation of motion trends.
You can read more here: https://www.mathworks.com/help/stats/principal-component-analysis-pca.html
Hope this helps you @Dalia
0 个评论
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Computer Vision with Simulink 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!