h a l f b a k e r yThis is what happens when one confuses "random" with "profound."
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We've all seen Rick Deckard and apparently the people on
CSI enhancing images to a ludicrous extent, enabling the
image to reveal objects on the other sides of walls and
under the floorboards or whatever. All of this is clearly
ludicrous. At the same time I still think my "gainy image
compression"
(see link) would work to some extent. I also
think this would.
I was recently perusing a picture of myself from a house I
lived in a few years ago and noted that because I happened
to know a specular reflective surface, to wit a metallic zip
fastener, was facing a scene including a carpet, a piano
stool, upright piano and street scene through a window, I
was able to glean which teeth were reflecting which
objects. At the same time the lenses on a pair of glasses
reflected a much more easily enhanced image of the same
scene.
Just now, I went into the kitchen to note the presence of a
chrome milk jug, kettle, cutlery, a wine glass, metallic
draining board and sink reflected from the aforesaid
chrome jug, and was able to infer from those reflections
and refractions while facing away from the window that
there was a window with a pair of curtains, some kind of
garden and a partly clouded sky.
Therefore, it seems to me, and don't ask me how, that if
something like raytracing could be performed in reverse in
order to reconstruct scenes which are not obviously in the
image and away from which the camera is facing. I can
vaguely suggest how but there would need to be a
mechanisable bit which I have little idea how to approach.
It amounts to computer vision and then some. The
specular reflections in an image clearly depend on the
angle of the surfaces from which they reflect. If there's a
way of identifying areas of reflection and specular
reflection and calculating those, the likes of refraction
through transparent media and off glass, metal and smooth
surfaces of other kinds could be used to reconstruct the
unseen parts of a photographic image. The same applies
to video, but in this case the job may be easier because
movement would give clues as to the shapes and angles
concerned.
I realise this is a big vague blob of an idea with a few little
details worked out round the edges but surely this could be
done one day, couldn't it?
Reflectoscope
Reflectoscope [theircompetitor, Jul 23 2017]
Gainy image compression
Gainy_20image_20compression Aimless self-promotion [nineteenthly, Jul 23 2017]
Camera Sees around Corners
http://www.popularm...ees-around-corners/ Similar specular goings on here, with lasers [Zeuxis, Jul 24 2017]
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I think a truly specular reflection carries very little information. However, there are plenty of instances of people recovering images from reflections - for instance, in a high-resolution photo of a face, you can recover an image of the photographer from the reflections in the subject's eyes. |
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"Gimme a hard copy right there". |
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Must've been the glitter wot did it, [ of ]. |
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"Not fish ... snake scale !!" |
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Over the last few months, I've been considering on
and off (well, twice, once a few months ago and the
second time the other day) the issue of robots
understanding mirrors and other reflective objects.
There's the well-known mirror test that's used on
animals (and has been used on at least one robot
model, which has a specific optical signal that it uses
to differentiate the image of itself in the mirror from
another similar robot it sees) but there are more basic
levels than that. Here's what I've been thinking
about: |
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Level 0.5: The robot can be told that something is a
mirror, and then understands that objects that appear
to be behind the mirror actually aren't where they
appear, and that it should not attempt to interact
with them physically through the mirror. |
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Level 1: The robot is capable of identifying a mirror
(or other reflective object) in its visual field, and
understands that a mirror is something that distorts
its visual view of the world, in that objects that appear
to be behind the mirror actually aren't where they
appear, and that it should not attempt to interact
with them physically through the mirror. |
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Level 2: The robot understands that things it sees in
the mirror correspond to objects on this side of the
mirror, and can learn information about objects via
the mirror that it could not learn by direct line-of-
sight observation (e.g. the appearances of backs of
objects, the locations of hidden objects). |
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Higher levels that I forget the order and details of
since thinking them up: The robot recognizes itself in
the mirror without having to use a special signal. The
robot can coordinate its actions by viewing itself/the
environment via the mirror. The robot understands
the visual effects of curved mirrors, dirty mirrors,
partially reflective mirrors, etc., and how to work with
them. |
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Similar comprehension levels could be defined for
refractive objects, periscopes, etc. |
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[Level 0.1] Robot drives through the mirror. Says "Oh, no.
Not again!" |
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[Level 5.0] Robot says " Do you think my assembly looks
too big in this?" |
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Mirror mirror on the wall, who's the Faradayest of them all? (+) |
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[Level 2.0] Robot drives through the mirror being carried by two men ... then hits a fruit cart ... a rack of clothes ... a pile of empty cardboard boxes ... some flimsy wooden crates full of live chickens ... |
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