Thanks Linas, I do have the vision part working now. (sending ROS messages
for FACES, LOST_FACE and NEW_FACE).
 However I don't have the Eva/Sophia head working yet, I'm working towards
that, any help is welcome.

On Fri, Feb 25, 2022 at 12:32 PM Linas Vepstas <[email protected]>
wrote:

> Hi Mark,
>
> Preface for anyone else reading this: Mark is dusting off the old Hanson
> Robotics code for Eva.  One of the subsystems was face-tracking. When your
> webcam was calibrated correctly, then Eva had this uncanny ability to look
> at you from out of the screen: her eyes would track your position. It was
> really pretty cool, as you really got the sense she was looking at you.
>
> Anyway, it seems that Mark has this code working again, or almost working?
> A related gotcha is some of the camera-transforms in Blender needed to be
> adjusted, to accurately reflect that you sit about an arms-length away from
> your computer screen, which is small on laptops but big on desktops, etc.
> so eye tracking didn't work right if all these dimensions weren't accounted
> for. It was kind of tricky to get it all right.  But when it worked, it was
> really cool and even spine-tingling.
>
> What about face recognition? This too worked, in a limited setting: she
> could recognize a handful of faces, and pull out the names of those people
> from a database.  There are then three questions; how did this work, back
> then, how can it be made to work in the short term, and what is the correct
> long-term architecture?
>
> First part: "how did it work back then"? See
> https://github.com/opencog/ros-behavior-scripting The code might be
> bit-rotted, but it worked. (There was some radical meatball surgery towards
> the end; this might need to be revisited.)  The general philosophy, back
> then, was that:
> * The 3D locations of objects (such as faces) would be stored in the
> opencog "spacetime server".
> * The only reason to do this was so that there could be an API for verbal
> propositions: near, far, next to, behind, in front of, to the left of, etc.
> that the language subsystem could use. That API was never built.
> * The AtomSpace would hold all information about everything, e.g face #135
> is actually Ben who is NN years old, lives in YY, loves robots, and is
> standing "next to" David (as reported by the space-server)
> * Why the AtomSpace? Because its the obvious place where current sensory
> info: sight & sound, can be integrated in with long-term knowledge and
> memories, as well as the dialog/language subsystem, as well as controlling
> movement and behaviour (turn left, right, blink and smile..)
> * Unfortunately, integrating the senses together with the background
> knowledge is hard. It was done in an ad hoc manner, it was
> under-documented, hard to use, hard to understand.  An adequate framework
> was never developed. This is not something one college student can knock
> out in a few weeks. The foundation for that framework is in the
> ros-behavior-scripting git repo. Fragments are in other places, I'd have to
> dig them up.
>
> So ... back to the question: face recognition:  Sure. Whatever. If you
> have a module that can recognize faces, then sure, whatever, have it
> forward that info to the AtomSpace.  That's the easy part.  The hard part
> is to integrate it into the speech subsystem.  So, when a new person
> appears in front of the camera, and says "Hi, my name is Mark", something
> has to extract the word "Mark", realize that "Mark" is someone's name,
> understand that there is probably a real-time correlation between that name
> and what the camera is seeing, take a snapshot of what the camera is
> seeing, and permanently tag that image with the name "Mark". To remember
> it. So that, minutes later, when Mark leaves the room and comes back, or
> months later, after a reboot, Eva still remembers what Mark looks like, as
> well as his favorite color, sports-team, childhood hero, mother's maiden
> name, last four digits of his soc sec and bank account #.
>
> I think all that is doable, and there are many different ways of doing the
> above, from quick short hacks to complicated theoretically-correct
> approaches ... but .. this email is too long, so, let me leave it at that.
>
> -- Linas
>
> On Fri, Feb 25, 2022 at 8:16 AM Mark Wigzell <[email protected]>
> wrote:
>
>> Hi folks, my subject stems from having recently done a deep-dive into the
>> pi_vision implementation. The original face detection and tracking was
>> rusted, so I revamped it. In doing so I added in a hook for eventually
>> augmenting the "new_face" message with some face recognition. I was
>> informed that rather than splicing in some face detection algorithm at the
>> pi_vision level, the "vision" would be to have the image elements reach the
>> atomspace, and thus allow recognition to occur at a more basic level.
>>
>> Therefore, pursuant to the above, I'm asking for a high level description
>> of how AGI vision could be accomplished. Perhaps we can also address
>> the question of why face detection and tracking are "ok" but face
>> recognition is not? Maybe all processing should be done at a lower level?
>>
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>>
>
>
> --
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