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So here's the sound that we played in the room.
And this is a high-speed video we recorded of that bag of chips.
Again it's playing.
There's no chance you'll be able to see anything going on in that video just by looking at it,
but here's the sound we were able to recover just by analyzing the tiny motions in that video.
I call it Thank you.
I call it the visual microphone.
We actually extract audio signals from video signals.
And just to give you a sense of the scale of the motions here,
a pretty loud sound will cause that bag of chips to move less than a micrometer.
That's one thousandth of a millimeter.
That's how tiny the motions are that we are now able to pull out
just by observing how light bounces off objects and gets recorded by our cameras.
We can recover sounds from other objects, like plants.
And we can recover speech as well.
So here's a person speaking in a room.
Michael Rubinstein: And here's that speech again recovered just from this video of that same bag of chips.
这是我们在房间中播放的声音。
这是我们摄制的薯片袋的高速视频。
同样,
您凭肉眼是看不出来什么的,
但是我们可以通过分析视频中微小的振动恢复出原有的声音。
我叫它-谢谢。
我叫它视觉麦克风。
实际上我们从视频信号中提取了音频信号。
为了让您了解运动的大小,
一个特别大的声音可以导致薯片袋一微米的变化。
也就是千分之一毫米。
这就是我们能够提取出来的微小运动
仅仅是通过摄像机录制的视频观察光线在物体上的变化。
我们可以从物体上重构出原声音,如植物。
我们也可以重构出讲话。
这是一个人在房间中讲话。
迈克尔鲁宾斯坦:这是一个讲话这段视频同样是由那个薯片袋重构出声音。
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