Lol, didn't read this one, jinxing with these people. - matt

On Thu, Oct 17, 2013 at 1:43 PM, Aaron Heller <hel...@ai.sri.com> wrote:

> Interesting paper in PNAS, from July. I believe it is open access, so
> anyone can read/download.   Aaron
>
> http://www.pnas.org/content/110/30/12186.short
>
> The supplemental information (SI) shows some of the equipment and more
> math.
>
> I. Dokmanić, R. Parhizkar, A. Walther, Y. M. Lu, and M. Vetterli, “Acoustic
> echoes reveal room shape,” Proceedings of the National Academy of Sciences,
> vol. 101, no. 30, pp. 12186–12191, Jul. 2013.
>
>
> Abstract
>
> Imagine that you are blindfolded inside an unknown room. You snap your
> fingers and listen to the room’s response. Can you hear the shape of the
> room? Some people can do it naturally, but can we design computer
> algorithms that hear rooms? We show how to compute the shape of a convex
> polyhedral room from its response to a known sound, recorded by a few
> microphones. Geometric relationships between the arrival times of echoes
> enable us to “blindfoldedly” estimate the room geometry. This is achieved
> by exploiting the properties of Euclidean distance matrices. Furthermore,
> we show that under mild conditions, first-order echoes provide a unique
> description of convex polyhedral rooms. Our algorithm starts from the
> recorded impulse responses and proceeds by learning the correct assignment
> of echoes to walls. In contrast to earlier methods, the proposed algorithm
> reconstructs the full 3D geometry of the room from a single sound emission,
> and with an arbitrary geometry of the microphone array. As long as the
> microphones can hear the echoes, we can position them as we want. Besides
> answering a basic question about the inverse problem of room acoustics, our
> results find applications in areas such as architectural acoustics, indoor
> localization, virtual reality, and audio forensics.
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