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Eulerian Video Magnification
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- Опубликовано: 6 фев 2019
- This is a short video about Eulerian Video Magnification. The project was done by Nic Dorner at the Berne University of Applied Sciences. It shows how you can read a persons heart rate out of a face video.
please release the code! i'd love to see how it's done
Nice! Seems like pretty easy to code. I had no idea that it was so simple.
You're our hero
This is the most concise explanation I have found about this particular topic.
What is the iterations on the x axis?
Great way to explain those papers !! 👏🏼👏🏼
Nice and simply put together thanks
OK, BUT, how do you know that 60 hz signal IS the heart rate?
AC line is also at 60 Hz. If you are overlaying that rate and doing what you do you are just superimposing line frequency on to the face and calling it the heart rate ;/ completely fubaring the truth in the process.
I'm not saying it isn't the case but this is far from proof that it works and also that it is not susceptible to noise.
You are claiming that if you isolate frequencies it says something about intrinsic behaviors in the image but there is no proof that it is or that it is not essentially stochastic alterations.
Literally if you isolate 60hz from any data and amplify it you get 60hz in the data. If you take any FT of any data and boost f hz then you are, well, boosting f hz. Since almost all data is noisy it will have 60hz noise in it in some form.
Essentially all you are doing is overlaying a 60hz signal on to an image and claiming that amplified visual effect is due to something else that may or may not be 60hz.
This is quite dangerous. You are potentially attributing things to other things when there is no real connection and the only reason they are convincing is because what you are picking out is what you are looking for.
I've seen several of these of these videos but I've never anything that isn't actually dynamically changing and which conclusively proves this isn't just looking for nails. Yes, you can take the FT of an image and then amplify various frequencies and even amplify the peak frequencies. In theory, as long as those frequencies truly represent intrinsic changes in the data set then it should work. Obviously in idealized cases it looks to work but I'm starting to think this method isn't very robust as claimed. The FT is very susceptible to noise. If I'm not mistaken there are more advanced methods that use AI to increase robustness.
Its not 60Hz. Its 1HZ, which is 60 per second. I dont see a resource of 1Hz in these videos but if you are skeptical just do it yourself, people got their thesis on this for fucks sake
@@Eren-he5dt 60 per second is 60 Hz moron.
For fucks sake, can you even compute a FFT?