# Crumpling Sound Synthesis | Two Minute Papers #115

## Метаданные

- **Канал:** Two Minute Papers
- **YouTube:** https://www.youtube.com/watch?v=PMSV7CjBuZI
- **Дата:** 17.12.2016
- **Длительность:** 3:52
- **Просмотры:** 13,836
- **Источник:** https://ekstraktznaniy.ru/video/14735

## Описание

The paper "Crumpling Sound Synthesis" is available here:
http://www.cs.columbia.edu/cg/crumpling/

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## Транскрипт

### Segment 1 (00:00 - 03:00) []

dear fellow Scholars this is 2minute papers with car today we are going to crush some soda cans in the footage that you see here the animations are performed by an already existing algorithm for thin shell deformations and for a complete sensorial experience this piece of work aims to synthesize sound for these phenomena sounds for crumpling up all kinds of candy wraps foils and plastic bags a lofty Noble goal loving it however this problem is extraordinarily difficult the reason is that these campling simulations are amazingly detailed and even if we knew all the physical laws for the sound synthesis which is already pretty crazy it would still be a fruitless Endeavor to take into consideration every single thing that takes place in the simulation we have to come up with ways to cut Corners to decrease the execution time of our algorithm running a naive exhaustive search would take tens of hours for only several seconds of footage and the big question is of course what can we do about it and before we proceed just a quick reminder that the geometry of these models are given by a lot of connected points that people in computer Graphics like to call vertices the sound synthesis takes place by observing the changes in the stiffness of these models which is the source of the crumpling noise normally our sound simulation scales with a number of vertices and it is abund AB L clear that there are simply too many of them to go through one by one to this end We should strive to reduce the complexity of this problem first we start with identifying and discarding the less significant vibration modes beyond that if in one of these vertices we observe that a similar kind of buckling behavior is present in its neighborhood we group up these vertices into a patch and we then forget about the vertices and run the sound synthesis on these patches and of course the number of patches is significantly less than the number of vertices in the original model in this footage you can see some of these patches and it turns out that the execution time can be significantly decreased by these optimizations with these techniques we can expect results in at least five times quicker but if we are willing to introduce slight degradations to the quality of the sounds we can even go 10 times quicker with barely perceptible changes to evaluate the quality of the solutions there is a user study presented in the paper and the Pinnacle of all tests is of course when we let reality be our judge everything so far sounds great on paper but how does it compare to what we experience in reality wow truly excellent results suffice to say they are absolutely crushing it and we haven't even talked about stochastic enrichment and how one of these problems can be solved optimally via dynamic programming if you are interested make sure to have a look at the paper thanks for watching and for your generous support and I'll see you next time