New Scientist - 09.11.2019

(Grace) #1
9 November 2019 | New Scientist | 45

a laser operating in the terahertz range,
which is midway between infrared light and
microwaves. Terahertz light can penetrate
materials and, unlike X-rays, it can also
distinguish between white and black tones.
From the precise arrival time of photons
that are reflected, the MIT researchers could
select, by depth, any page up to nine sheets
down, and scan its text. The capability could
be a boon for historians looking to investigate
delicate cultural artefacts.
Or, returning to vehicle safety, how
about being able to see through fog?
Last year, Guy Satat, then a PhD student in
Raskar’s group, noticed that the wavelength
of photons that have scattered off fog
particles is skewed in a distinct way. The
skewed photons can be discarded, leaving
only those scattered from the object. Add
some sort of photon-return timing system
to judge depth and the fog is lifted.
This sort of technology is still in its infancy,
but it is already clear it will save lives – and
who knows what other applications are hiding
around the corner? ❚

to get used to it, and push back against any
uses they consider inappropriate.
In any case, it is hard to stem the flow
of ideas, especially given a $28 million
well of funding from the US Defense Advanced
Research Projects Agency shared by many
of the research groups. Another concept
Goyal is working on is a combination of the
penumbra and laser approaches, which he
expects will make round-the-corner imaging
more flexible and reduce acquisition time.
Others, meanwhile, are using sound or Wi-Fi
signals rather than light to see into hidden
spaces (see “Hearing the sights”, left).
Then there are ways to employ the
technology to see objects hidden not outside,
but inside the frame. In 2016, Raskar and his
colleagues exposed a printed manuscript to

Jon Cartwright is a consultant
for New Scientist based in
Bristol, UK

“ A 3-D image


of a room can


be constructed


from the


shadow cast by


a houseplant”


SOURCE: doi.org/gftrn2


  1. A screen shows an
    image that is hidden
    from a camera’s view
    2. Light and shade from
    the image, obstructed by a
    chair, fall on the opposite
    wall. The camera takes a
    picture of the shadow
    3. An algorithm
    analyses the
    shadow, teasing
    out the visual
    information
    encoded in the
    pattern of light
    rays blocked out
    by the chair, to
    reconstruct the
    out-of-sight image


In the shadows
How an ordinary digital camera can see a hidden image

that work with textured, rather than just
featureless, surfaces. He even has
preliminary results for two-dimensional
images from one-dimensional corners
without extra occluders. Position in the
second dimension can be gauged from the
relative brightness of the scattered light, he
says. “It’s less robust, but we’ve had success.”
Meanwhile, Torralba, Freeman and
their colleagues have shown that a
three-dimensional image of a room can
be reconstructed merely from the shadow
cast by a houseplant. This works in the same
way as the corner-imaging technique, in that
different points of the plant’s shadow reveal
information about different portions of the
room. The distinction is that the computation
required is far more complicated here,
because the shadow is cast by leaves and
stems sprouting in all directions. In fact, the
image they created was only made possible
thanks to a painstaking calibration procedure,
which involved shining light onto the plant
from every point within the room beforehand,
to work out the geometrical relationship
between shadow and hidden scene.
With the science moving so fast, it is
tempting to speculate what these algorithms
could do in the future. Ye points out that
artificial intelligence is increasingly able to
work out geometry from still photographs,
without any calibration. Combined with
the ability to interpret shadows, this
potentially means that any photo could
betray something of the scene outside
the original frame. “Any camera has a
limited field of view,” says Ye. “Even just
for security or forensics, it would be
incredible if you could increase that.”
Because the recording equipment need be
nothing special, the images don’t have to be
new, either. Imagine being able to shed light,
retrospectively, on the context of rare historical
photos or video footage, or contemporary
photos presented as fake news. “It’s definitely
plausible,” says Goyal. “It’s all just post-
processing. You just need high resolution.”
Equally plausible, of course, are more
nefarious uses, such as spying on people who
believe they are out of sight. “I’ve thought a lot
about this and I don’t think people should be
too concerned,” says Ye. “These techniques
are currently super-sensitive to things like
camera motion, which is why we’ve mostly
used fixed cameras. Even just for very slowly
moving cameras, things become very hard,
very quickly.” Although the technology is
progressing fast by scientific standards, she
adds, societies will still have plenty of time

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