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Program Allows Ordinary Digital Camera To See Around Corners (theguardian.com)
An anonymous reader quotes a report from The Guardian: Science may never tell us what lies round the next corner, but researchers have come up with the nearest thing: a computer program that turns a normal digital camera into a periscope. In a demonstration of "computational periscopy" a U.S. team at Boston University showed they could see details of objects hidden from view by analyzing shadows they cast on a nearby wall. Vivek Goyal, an electrical engineer at the university, said that while the work had clear implications for surveillance he hoped it would lead to robots that could navigate better and boost the safety of driverless cars.
In the latest feat, Goyal and his team used a standard digital camera and a mid-range laptop. The researchers, writing in the journal Nature, describe how they pieced together hidden scenes by pointing the digital camera at the vague shadows they cast on a nearby wall. If the wall had been a mirror the task would have been easy, but a matt wall scatters light in all directions, so the reflected image is nothing but a blur. They found that when an object blocked part of the hidden scene, their algorithms could use the combination of light and shade at different points on the wall to reconstruct what lay round the corner. In tests, the program pieced together hidden images of video game characters -- including details such as their eyes and mouths -- along with colored strips and the letters "BU." The program takes about 48 seconds to work out a hidden scene from a digital image, but the researchers believe it could be sped up with a faster computer. Eventually, it may be fast enough to run on video footage.
Goyal also said "it is even conceivable for humans to be able to learn to see around corners with their own eyes; it does not require anything superhuman."
In the latest feat, Goyal and his team used a standard digital camera and a mid-range laptop. The researchers, writing in the journal Nature, describe how they pieced together hidden scenes by pointing the digital camera at the vague shadows they cast on a nearby wall. If the wall had been a mirror the task would have been easy, but a matt wall scatters light in all directions, so the reflected image is nothing but a blur. They found that when an object blocked part of the hidden scene, their algorithms could use the combination of light and shade at different points on the wall to reconstruct what lay round the corner. In tests, the program pieced together hidden images of video game characters -- including details such as their eyes and mouths -- along with colored strips and the letters "BU." The program takes about 48 seconds to work out a hidden scene from a digital image, but the researchers believe it could be sped up with a faster computer. Eventually, it may be fast enough to run on video footage.
Goyal also said "it is even conceivable for humans to be able to learn to see around corners with their own eyes; it does not require anything superhuman."
I have found doing this requires more then the sense of sight to do this. We can hear someone walking, if the floor is elevated we can feel it shaking, If we were doing this with a Video Camera on an RC Car. chances are we would get surprised
If something is so important that you feel the need to post it on the internet... It probably isn't that important.
Goyal also said "it is even conceivable for humans to be able to learn to see around corners with their own eyes; it does not require anything superhuman."
I'd think this was more of ASSUMING or taking a guesstimate of what was around the corner. Actually seeing would be superhuman. Still a cool idea if we'd have something that could do this in real time at a fast pace. I'd assume it'll be a bit more accurate than what we'd guess, especially if we were excited/worried/scared/etc.
How does it account for differing light sources? Depending on where the light is coming from an object can cast all kinds of shadows.
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A pointless technology in China. It would get ripped out of your hand by the throng coming around the corner. A better invention might just be a fake periscope with a video of a throng coming around a corner. And you could use filters to decorate the throng! =)
And there'd be an option for musical accompaniment. A "Throng Song", if you will...
Get Sisqo to do it and you can have the Throng Thong Song.
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If we could learn to make sense of fuzzy images, there would be no need for glasses.
This. Unlike the realm of sensory perception available to humans and other living organisms, this technology appears to rely upon refraction of light off of a surface facing the camera(s).
The advantage of any tech that mimics the senses of sentient creatures is processing speed, as it now routinely surpasses organic abilities. Perhaps the real leap forward is the yet to be refined sensory abilities beyond what discovered life is capable of.
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What, did they recycle DECs Alpha processors for this application to warrant a "digital" logo on this story? Sheesh, kids these days...
You just face the camera at 90 degrees on the selfie stick. So simple! amazing no one thought of this before.
Some drink at the fountain of knowledge. Others just gargle.
Where in a scene with a camera and a projector, the scene can be from the point of view of either the camera or projector.
Nice post. But one nitpick:
Unlike the realm of sensory perception available to humans and other living organisms, this technology appears to rely upon reflection of light off of a surface facing the camera(s).
FTFY, Light refracts when it passes through a medium, not when it bounces off it.
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As you may have learned from the recent lunar eclipse, a shadow is composed of a penumbra and umbra. The light is completely occluded in the umbra, partially occluded in the penumbra. So if you consider any single point source of light from the hidden scene, certain parts of the wall receive light from it, other parts do not. The algorithm then works from that to back out the original scene (light sources). "Accounting for differing light sources" is exactly what it's doing to figure out the original scene.
Where your comment is relevant is that the object creating a shadow can be of arbitrary shape. In this case it was a fixed and known shape, which simplified computing the image. I dunno if this technique would work with an arbitrary scene and an arbitrary-shaped object blocking the light. If the object were close enough to cast an umbra, you could deduce its shape and refine the image over multiple iterations (basically guess small changes in the shadow object's shape to see if it results in the algorithm yielding a sharper picture). But if you're only getting a penumbral shadow, I'm not sure if there's an algorithmic solution that'll work for all scenes and all blocking shapes.
The program takes about 48 seconds to work out a hidden scene from a digital image, but the researchers believe it could be sped up with a faster computer.
Yes a faster computer "could" speed up the process. Great reporting there!
Thats like saying a faster car could get me to work sooner. It might, but I suspect the cars in front of me and all the lights would prevent me from fully utilizing the speed of any car. However, re-evaluating the route I take, or using a bicycle might utilize the current car I have much better than getting a faster one.
Whenever writing something critical, first make it work. Then make it so that anyone can understand it in detail. Then profile and find the bottlenecks. Finally remove or mitigate those bottlenecks as much as possible so that it still works and can be understood. A faster CPU should be the last resort.
Enhance. Enhance. Enhance.
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my AI tells me its true
Hardcopy is so 2019
Just like on CSI, when they find a glint of light reflecting off a lamp, magnify, and enhance the image so they can figure out who the killer was. Easy peasy!