A camera that can see around corners | David Lindell

92,088 views ・ 2020-04-21

TED


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Transcriber: Ivana Korom Reviewer: Krystian Aparta
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In the future,
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self-driving cars will be safer and more reliable than humans.
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But for this to happen,
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we need technologies that allow cars to respond
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faster than humans,
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we need algorithms that can drive better than humans
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and we need cameras that can see more than humans can see.
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For example, imagine a self-driving car is about to make a blind turn,
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and there's an oncoming car
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or perhaps there's a child about to run into the street.
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Fortunately, our future car will have this superpower,
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a camera that can see around corners to detect these potential hazards.
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For the past few years as a PhD student
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in the Stanford Computational Imaging Lab,
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I've been working on a camera that can do just this --
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a camera that can image objects hidden around corners
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or blocked from direct line of sight.
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So let me give you an example of what our camera can see.
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This is an outdoor experiment we conducted
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where our camera system is scanning the side of this building with a laser,
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and the scene that we want to capture
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is hidden around the corner behind this curtain.
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So our camera system can't actually see it directly.
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And yet, somehow,
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our camera can still capture the 3D geometry of this scene.
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So how do we do this?
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The magic happens here in this camera system.
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You can think of this as a type of high-speed camera.
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Not one that operates at 1,000 frames per second,
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or even a million frames per second,
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but a trillion frames per second.
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So fast that it can actually capture the movement of light itself.
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And to give you an example of just how fast light travels,
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let's compare it to the speed of a fast-running comic book superhero
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who can move at up to three times the speed of sound.
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It takes a pulse of light about 3.3 billionths of a second,
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or 3.3 nanoseconds,
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to travel the distance of a meter.
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Well, in that same time,
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our superhero has moved less than the width of a human hair.
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That's pretty fast.
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But actually, we need to image much faster
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if we want to capture light moving at subcentimeter scales.
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So our camera system can capture photons
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at time frames of just 50 trillionths of a second,
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or 50 picoseconds.
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So we take this ultra-high-speed camera
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and we pair it with a laser that sends out short pulses of light.
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Each pulse travels to this visible wall
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and some light scatters back to our camera,
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but we also use the wall to scatter light around the corner
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to the hidden object and back.
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We repeat this measurement many times
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to capture the arrival times of many photons
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from different locations on the wall.
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And after we capture these measurements, we can create
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a trillion-frame-per-second video of the wall.
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While this wall may look ordinary to our own eyes,
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at a trillion frames per second, we can see something truly incredible.
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We can actually see waves of light scattered back from the hidden scene
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and splashing against the wall.
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And each of these waves carries information
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about the hidden object that sent it.
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So we can take these measurements
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and pass them into a reconstruction algorithm
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to then recover the 3D geometry of this hidden scene.
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Now I want to show you one more example of an indoor scene that we captured,
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this time with a variety of different hidden objects.
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And these objects have different appearances,
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so they reflect light differently.
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For example, this glossy dragon statue reflects light differently
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than the mirror disco ball
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or the white discus thrower statue.
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And we can actually see the differences in the reflected light
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by visualizing it as this 3D volume,
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where we've just taken the video frames and stacked them together.
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And time here is represented as the depth dimension of this cube.
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These bright dots that you see are reflections of light
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from each of the mirrored facets of the disco ball,
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scattering against the wall over time.
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The bright streaks of light that you see arriving soonest in time
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are from the glossy dragon statue that's closest to the wall,
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and the other streaks of light come from reflections of light from the bookcase
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and from the statue.
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Now, we can also visualize these measurements frame by frame,
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as a video,
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to directly see the scattered light.
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And again, here we see, first, reflections of light from the dragon,
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closest to the wall,
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followed by bright dots from the disco ball
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and other reflections from the bookcase.
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And finally, we see the reflected waves of light from the statue.
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These waves of light illuminating the wall
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are like fireworks that last for just trillionths of a second.
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And even though these objects reflect light differently,
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we can still reconstruct their shapes.
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And this is what you can see from around the corner.
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Now, I want to show you one more example that's slightly different.
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In this video, you see me dressed in this reflective suit
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and our camera system is scanning the wall at a rate of four times every second.
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The suit is reflective,
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so we can actually capture enough photons
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that we can see where I am and what I'm doing,
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without the camera actually directly imaging me.
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By capturing photons that scatter from the wall to my tracksuit,
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back to the wall and back to the camera,
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we can capture this indirect video in real time.
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And we think that this type of practical non-line-of-sight imaging
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could be useful for applications including for self-driving cars,
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but also for biomedical imaging,
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where we need to see into the tiny structures of the body.
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And perhaps we could also put similar camera systems on the robots
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that we send to explore other planets.
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Now you may have heard about seeing around corners before,
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but what I showed you today would have been impossible
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just two years ago.
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For example, we can now image large, room-sized hidden scenes outdoors
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and at real-time rates,
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and we've made significant advancements towards making this a practical technology
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that you could actually see on a car someday.
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But of course, there's still challenges remaining.
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For example, can we image hidden scenes at long distances
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where we're collecting very, very few photons,
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with lasers that are low-power and that are eye-safe.
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Or can we create images from photons
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that have scattered around many more times
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than just a single bounce around the corner?
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Can we take our prototype system that's, well, currently large and bulky,
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and miniaturize it into something that could be useful
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for biomedical imaging
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or perhaps a sort of improved home-security system,
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or can we take this new imaging modality and use it for other applications?
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I think it's an exciting new technology
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and there could be other things that we haven't thought of yet
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to use it for.
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And so, well, a future with self-driving cars
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may seem distant to us now --
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we're already developing the technologies
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that could make cars safer and more intelligent.
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And with the rapid pace of scientific discovery and innovation,
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you never know what new and exciting capabilities
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could be just around the corner.
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(Applause)
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