Please for the love of all that is holy keep making these videos. Why is it that almost all the best foundational math content used in Computer Vision applications I can find online comes from someone at The University of Washington? Y'all are awesome!
*Thanks! Subscribed! Was so over people and chatgpt basically saying nyquist was enough to use an RC filter with to get a smooth and accurate audio wave. Today grilled chatgpt and it mentioned one of those, but not the other ones. Also it mentioned polynomial interpolation and delta sigma modulation. Sadly a college (surprisingly a college based in THE USA) committed HORRIBLE discrimination against ME this semester and the past 2 calendar years, so I have been working on new electronics products and learning DSP and so on without a formal college. The specific type of discrimination those scumbags perpetrated was what most humans would probably call RELIGIOUS discrimination. I did Stanford doctoral student tutoring (in software engineering) without having a University or college degree, so it was ridiculous to have tried to register at a crappy college anyway. I'm building a mini computer company now (THANKFULLY complete with full color touch displays) instead of refining plutonium for vengeance against those corrupt scumbags. If have any friends that are profs at MIT or Georgia Tech or Cal Tech, thanks in advance for introducing those to Me soon (I have been building a portfolio to apply)!*
1:16 multiplying the sample values(0.5) times the num of blue samples( i understand you gotta sum of their values) 0.5*1.2 = 0.6 and 0.5*2 = 1... then i need to sum the both results 1.6, and that would be the 50% from A way towards B.. and when they are .25 and .75 it goes like --> 1.2*0.25 + 2 *0.75 = 1.8 ..
Could you please explain how much space does it have to take from each calculation? Or How much jumps? Also are the calculations from the filter similar to the following process?: When the filter is between the two blue dots Does it multiply the two values in the one column then add them together in the middle of the filter? Is this how it works?
I arrived at your video from the audio world, where there is a fellow who has made interpolation filters for reconstructing analog audio waveforms from digital samples. While an infinite-length sinc function can perfectly reconstruct a bandlimited signal from its samples, what is the interpolation error for finite-length sinc functions? This fellow (Rob Watts / Chord Electronics) uses upwards of a million (!!) taps of a sinc function to reconstruct the signal. With fewer taps (say, 100) would the estimation of inter sample peaks (like those encountered with drums) be shifted in time upon reconstruction?
![เปิด อาณาจักร หมื่นล้าน "สาระตั้ม" l [Nickynachat]](http://i.ytimg.com/vi/3XE0nPF4YkQ/mqdefault.jpg)
Please for the love of all that is holy keep making these videos. Why is it that almost all the best foundational math content used in Computer Vision applications I can find online comes from someone at The University of Washington? Y'all are awesome!
FINALLY!!!! THERE'S A CLEAR!! AND FREINDLY EXPLANATION OF WHAT I NEEDED TO COMPLETE MY CODE!!!!!!!!!!!!!!!!! THANK YOU SO MUCH!!!!!!!!!!!!!!!!!!
What a beautifully simplified way to visualize the working of kernels and its relation to interpolation. WAW!
I really think the video is underestimated... it is clear, easy to understand, and comprehensive
*Thanks! Subscribed! Was so over people and chatgpt basically saying nyquist was enough to use an RC filter with to get a smooth and accurate audio wave. Today grilled chatgpt and it mentioned one of those, but not the other ones. Also it mentioned polynomial interpolation and delta sigma modulation. Sadly a college (surprisingly a college based in THE USA) committed HORRIBLE discrimination against ME this semester and the past 2 calendar years, so I have been working on new electronics products and learning DSP and so on without a formal college. The specific type of discrimination those scumbags perpetrated was what most humans would probably call RELIGIOUS discrimination. I did Stanford doctoral student tutoring (in software engineering) without having a University or college degree, so it was ridiculous to have tried to register at a crappy college anyway. I'm building a mini computer company now (THANKFULLY complete with full color touch displays) instead of refining plutonium for vengeance against those corrupt scumbags. If have any friends that are profs at MIT or Georgia Tech or Cal Tech, thanks in advance for introducing those to Me soon (I have been building a portfolio to apply)!*
Omg. Years of formulae finally resolved.
This was a good one. Cheers!
1:16 multiplying the sample values(0.5) times the num of blue samples( i understand you gotta sum of their values)
0.5*1.2 = 0.6 and 0.5*2 = 1... then i need to sum the both results 1.6, and that would be the 50% from A way towards B.. and when they are .25 and .75 it goes like -->
1.2*0.25 + 2 *0.75 = 1.8 ..
Can we extend the gaussian bell to infinity on both sides with, what would that look like, guess I will have to try.
Could you please explain how much space does it have to take from each calculation? Or How much jumps?
Also are the calculations from the filter similar to the following process?:
When the filter is between the two blue dots
Does it multiply the two values in the one column then add them together in the middle of the filter? Is this how it works?
Can clarify what saying that there is "mass" loss between those 2 gridpoints at about 02:40?
basically the curves are not too curvy with that filter. So we use filters like lanczos and cubic to fix that
I arrived at your video from the audio world, where there is a fellow who has made interpolation filters for reconstructing analog audio waveforms from digital samples. While an infinite-length sinc function can perfectly reconstruct a bandlimited signal from its samples, what is the interpolation error for finite-length sinc functions? This fellow (Rob Watts / Chord Electronics) uses upwards of a million (!!) taps of a sinc function to reconstruct the signal. With fewer taps (say, 100) would the estimation of inter sample peaks (like those encountered with drums) be shifted in time upon reconstruction?
hear me out. it'll be "Interpolation in 2.5 minutes" if you put the playback speed on 2x
hi