OK, well, if you just write a teensy sliver of code that simply turns the
head towards any direction where something "sufficiently salient" happened,
then sure, that makes for a livelier, more entertaining demo. And so maybe
that is worthwhile.

But it also keeps her at the "dumb robot" level, reacting to a stimulus
without any clue as to why -- its like a single-neuron circuit -- whenever
one end of the neuron gets tickled, the other end turns a motor.   I want
to move past single-neuron reactive circuitry.   I mean, doors that swing
out of your way when you approach them were were in all the supermarkets by
the 1960's -- turning your head to look at something "salient" is at about
the same level of sophistication.  Its been 50 years. Yes, get to that, but
then go farther.

--linas

On Tue, Aug 9, 2016 at 1:08 AM, Ben Goertzel <[email protected]> wrote:

> Hi LInas, many of your suggestions are good ones and should be added to
> the list
>
> However, the "visual saliency" term was not invented by us -- and the
> addition of this saliency detector was especially suggested by David H
> because in his prior work he has found similar code to be useful with
> his robots....  So I guess I will trust him that it's a useful
> indicator to have, even though I agree with you that lots of other
> stuff is also useful
>
> The reason for adding a "Degree" was that without it, the saliency
> detector gave way too many false positives....  Having a degree lets
> us tune a threshold denoting what is salient enough to bother doing
> anything about...
>
> ben
>
> On Mon, Aug 8, 2016 at 1:01 PM, Linas Vepstas <[email protected]>
> wrote:
> > Oops, hit "send" on the email too soon.
> >
> > Perhaps the #1 most important thing on the list is the "sudden change in
> > brightness" detector.   During the demos people either cover her camera
> or
> > get up in her face, and say things like "can you see me now", and I would
> > really like to have the robot know when this is happening -- this is
> > probably the #1 most important demoable feature, more important than
> > saliency, movement, anything else.
> >
> > The #2 most important feature would be size-of-movement -- another thing
> > people do is to wave their hand directly in front of the camera:  From
> the
> > camera point of view, it would look like everything is moving everywhere
> --
> > the entire visual field is moving.  It doesn't have a location, because
> its
> > everywhere.  Again, this is a very important situation to recognize, and
> > relay to the robot.
> >
> > Both of the above should be easy to implement, and are more important,
> > demo-wise, than "saliency".
> >
> > --linas
> >
> >
> >
> > On Mon, Aug 8, 2016 at 2:49 PM, Linas Vepstas <[email protected]>
> > wrote:
> >>
> >> I have multiple issues with the so-called "saliency detector" in this
> pull
> >> request: https://github.com/hansonrobotics/HEAD/pull/117 that I'm
> thinking
> >> its better to discuss these in general, rather than simply in the
> context of
> >> one pull request.
> >>
> >> So:...
> >>
> >> On Wed, Jul 27, 2016 at 10:06 AM, natnaelargaw <
> [email protected]>
> >> wrote:
> >>>
> >>> the frequency of occurrence of a salient point with in a fixed turn
> >>> around time t. Further more, this method norm
> >>
> >>
> >> First off, the entire module seems to be mis-named -- it has nothing at
> >> all to do with "saliency" -- rather, the device seems to be a
> >> motion-tracker.
> >>
> >> Something can be highly salient, and completely still, but that is not
> >> what this does, based on the description in the README.
> >>
> >> Next, I'd like to see an API change. Put yourself in the place of
> opencog.
> >> Suppose you were blind-folded,  and someone was whispering in your ear:
> >> "hey, there is something important happening in the upper left. Oh
> wait, now
> >> its less important. ... now its more important, again!  Oh and also,
> there's
> >> something to your right, but its not very important."
> >>
> >> What can you possibly do with that data?  WTF? How can I possibly build
> a
> >> smart robot, when its effectively blind-folded, and has the above as
> sensory
> >> input?
> >>
> >> Thus, I suggest completely eliminating the "degree of saliency" measure
> >> from the API, and replacing it by three things: the *size* of the moving
> >> area, *how fast* its moving, and its color.
> >>
> >> Now, blind-folded, you get the message: "its very small, its moving
> >> slowly, and its black", and you might guess that its a fly buzzing
> around.
> >> "its big and its green and its up high and its bouncing" and you might
> guess
> >> its a helium balloon.  "its medium and its skin toned" and you might
> guess a
> >> waving hand or arm.
> >>
> >> Size speed and color should be easy to add, and would really be useful.
> >>
> >> For bonus points, I'd like a spinning/waving measure.  So, for example,
> a
> >> ceiling fan is "moving" but it never changes position. Similarly, a TV
> set
> >> in the background is "moving", without changing its location.  Likewise,
> >> anyone who is waving their hand -- the hand is moving but really stays
> in
> >> the same place.    This is very different from things the move and also
> >> change position -- someone walking across the room is both moving and
> >> changing position.
> >>
> >> Another bonus measure: is it moving up, down, sideways?
> >>
> >> There's four more bits of data that would be useful, unrelated to
> motion:
> >> -- a general sense of how bright or dark the room is,
> >> -- a general sense of the contrast in the image (sharp black/what, or
> >> mostly washed-out grey)
> >> -- sudden changes in overall lighting
> >> -- average color for the entire visual field.
> >>
> >> Sunlit rooms tend to have high contrast; lots of blue suggests the sky
> is
> >> visible; a sudden change of lighting suggests that someone put their
> hand
> >> over the camera.
> >>
> >> Apparently, people cover the camera with their hands a lot during demos,
> >> and I would really really like to know when that happens.
> >>
> >> There's other stuff I'd like to see, that would allow the robot to
> >> actually *learn*, but that is for a some future email.  The short
> version is
> >> that I would like to be able to send the detector some little tiny
> snippets
> >> of pseudo-code, and have it run that pseudo-code, and report when it
> >> triggers. The pseudo-code would consist of little algorithmic
> combinations
> >> of speed, color, movement, size, etc. and opencog would generate these
> and
> >> use them as feature detectors.  I.e. rather than hard-coding
> (hand-coding)
> >> the feature detectors, they would be generated dynamically, on the fly,
> by
> >> opencog itself, rather than by human programmers.   This is an idea for
> the
> >> future, though.  Important, but not urgent.
> >>
> >> -- Linas
> >>
> >>
> >>
> >
>
>
>
> --
> Ben Goertzel, PhD
> http://goertzel.org
>
> Super-benevolent super-intelligence is the thought the Global Brain is
> currently struggling to form...
>

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