CVPR 2022 Best Paper Honorable Mention: Dual-Shutter Optical Vibration Sensing

TLDR: They reconstruct sound using cameras and a laser beam on any vibrating surface, allowing them to isolate music instruments, focus on a specific speaker, remove ambient noises, and many more amazing applications.

►Read the full article: https://www.louisbouchard.ai/cvpr-2022-best-paper/
►Sheinin, Mark and Chan, Dorian and O'Toole, Matthew and Narasimhan,
Srinivasa G., 2022, Dual-Shutter Optical Vibration Sensing, Proc. IEEE
CVPR.
►Project page: https://imaging.cs.cmu.edu/vibration/
►My Newsletter (A new AI application explained weekly to your emails!): https://www.louisbouchard.ai/newsletter/

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this year i had the chance to be at cvpr

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in person and attend the amazing best

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paper award presentation with this

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fantastic paper i had to cover on the

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channel called dual shutter optical

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vibration sensing by mark shanin dorian

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chan mathew o'toole and srinivasa

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narasimhan in one sentence they

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reconstruct sound using cameras in a

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laser beam on any vibrating surface

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allowing them to isolate music

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instruments focus on a specific speaker

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remove ambient noises and many more

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amazing applications let's dive into how

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they achieve that and hear some crazy

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results but first allow me one minute of

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your time to introduce you to a

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fantastic company the sponsor of this

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video assembly ai assembly ai is a

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company that offers accurate apis for

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speech to text and audio intelligence

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you can use their apis to automatically

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transcribe and understand audio and

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video data in just a few lines of code

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and automatically convert asynchronous

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and live audio streams into text

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something extremely challenging to do

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and typically requiring robust and

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costly models of course it doesn't stop

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here assembly ai will also process your

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audio data and have informative feature

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representations allowing you to easily

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add text-based features like

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summarization content moderation topic

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detection and more all in one if you

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need to understand or transcribe audio

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or video data try assembly ai with the

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first link below

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let's start by listening to this example

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of what the method can achieve

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[Music]

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you could clearly hear the two

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individual guitars in each audio track

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this was made using not a recorded sound

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but a laser and two cameras equipped

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with rolling and global shutter sensors

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respectively it seems like tackling this

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task through vision makes it much easier

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than trying to split the audio tracks

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after recording it also means we can

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record anything through glasses and from

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any vibrating objects here they used

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their method on the speakers themselves

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to isolate the left and right speakers

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whereas a microphone will automatically

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record both and blend the audio tracks

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[Music]

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typically this kind of spy technology

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called visual vibrometry requires

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perfect lighting conditions and

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high-speed cameras that look like a

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camouflaged sniper to capture high-speed

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vibrations of up to 63 kilohertz here

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they achieve similar results with

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sensors built for only 60 and 130 hertz

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and even better they can process

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multiple objects at once still this is a

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very challenging task requiring a lot of

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engineering and great ideas to make it

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happen they do not simply record the

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instruments and send the video to a

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model that automatically creates and

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separates the audio they first need to

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understand the laser they receive and

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process it correctly they orient a laser

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on the surface to listen to then this

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laser bounces from the surface into a

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focus plane this focus plane is where we

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will take our information from not the

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instruments or objects themselves so we

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will analyze the tiny vibrations of the

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objects of interest through the laser

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response creating a representation like

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this

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this two-dimensional laser response

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pattern cut by our cameras called a

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speckle is then processed both globally

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and locally using our two cameras our

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local camera or the rolling shutter

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camera will capture frames at only 60

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fps so it will take multiple pictures

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and roll them on the y-axis to get a

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really noisy and inaccurate 63 kilohertz

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representation this is where the global

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shutter camera is necessary because of

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the randomness in the speckled imaging

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due to the roughness of the object's

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surface and its movements it will

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basically take a global screenshot of

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the same speckle image we used with our

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first camera and used this new image as

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a reference frame to isolate only

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relevant vibrations from the rolling

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shutter captures

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the rolling shutter camera will sample

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the scene row by row with a high

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frequency while the global shutter

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camera will sample the entire scene at

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once to serve as a reference frame and

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we repeat this process for the whole

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video

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and voila this is how they are able to

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split sound from a recording extract

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only a single instrument remove ambient

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noise or even reconstruct speech from

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the vibrations of a bag of chips

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mary had a little lamb this leaf was

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white as snow of course this is just a

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simple overview of this great paper and

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i strongly invite you to read it for

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more information congratulations to the

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authorities for the honorable mention i

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was glad to attend the event and see the

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presentation live i'm super excited to

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the future publications this paper will

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motivate i also invite you to double

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check all the bags of chips you may

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leave near a window or otherwise some

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people may listen to what you say thank

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you for watching the whole video and let

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me know how you'd apply this technology

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and if you see any potential risks or

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exciting use cases i'd love to discuss

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these with you and a special thanks to

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cvpr for inviting me to the event it was

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really cool to be there in new orleans

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with all the researchers and companies i

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will see you next week with another

amazing paper