Building A Sound Camera For Under $400

[Benn Jordan] had an idea. He’d heard of motion amplification technology, where cameras are used to capture tiny vibrations in machinery and then visually amplify it for engineering analysis. This is typically the preserve of high-end industrial equipment, but [Benn] wondered if it really had to be this way. Armed with a modern 4K smartphone camera and the right analysis techniques, could he visually capture sound?

The video first explores commercially available “acoustic cameras” which are primarily sold business-to-business at incredibly high prices. However, [Benn] suspected he could build something similar on the cheap. He started out with a 16-channel microphone that streams over USB for just $275, sourced from MiniDSP, and paired it  with a Raspberry Pi 5 running the acoular framework for acoustic beamforming. Acoular analyses multichannel audio and visualizes them so you can locate sound sources. He added a 1080p camera, and soon enough, was able to overlay sound location data over the video stream. He was able to locate a hawk in a tree using this technique, which was pretty cool, and the total rig came in somewhere under $400.

The rest of the video covers other sound-camera techniques—vibration detection, the aforementioned motion amplification, and some neat biometric techniques. It turns out your webcam can probably detect your heart rate, for example.

It’s a great video that illuminates just what you can achieve with modern sound and video capture. Think SIGGRAPH-level stuff, but in a form you can digest over your lunchbreak. Video after the break.

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Acoustic Camera Uses Many, Many Microphones

If you’re a human or other animal with two ears, you’ll probably find great utility in your ability to identify the direction of sounds in the world around you.  Of course, this is really just a minimal starting point for such abilities. When [John Duffy] set out to build his acoustic camera, he chose to use ninety-six microphones to get the job done.

The acoustic camera works by having an array of microphones laid out in a prescribed grid. By measuring the timing and phase differences of signals appearing at each microphone, it’s possible to determine the location of sound sources in front of the array. The more microphones, the better the data.

[John] goes into detail as to how the project was achieved on the project blog. Outlining such struggles as assembly issues, he also shares information about how to effectively debug the array, and just how to effectively work with so many microphones at once. Particularly impressive is the video of [John] using the device to track a sound to its source. This technology has potential applications in industry for determining the location of compressed air leaks, for example.

Overall, it’s a university research project done right, with a great writeup of the final results. [John]’s project would serve well as a jumping off point for anyone trying to build something similar. Phased array techniques work in RF, too, as this MIT project demonstrates. Video after the break.

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