I'm going to be showing a great deal of ignorance in this post, but who knows, 
it might help. 

I understand an issue recently discussed with embodiment concerns methods for 
processing visual input. It's well known that at this time sending raw video 
into atomspace is a bad idea and that humans have built in visual processors 
that assist our conscious minds in understanding what our eyes see. (Obvious 
simple example being that the image is preflipped). 

I understand opencog has (in some form) a python api which leads me to think 
using the visual processing engine OpenCV may not be a bad idea. It has a 
fantastic python api, allows for exporting specific data from raw video such as 
"33% of the screen is red", or  there are 2 lines in the field of view." it 
also has a PHENOMINAL foreground/background separation engine that allows only 
a processing of new or moving objects in the field of view. 

While a more mature opencog engine may prefer a more "raw" processor, I see 
OpenCV as a great place to start for getting useful information into atomspace 
quickly. 

I have yet to start work on this, heck, I have yet to fully learn the ropes of 
the current opencog system, but I wanted to at least drop the info here in case 
anyone else had comments or wanted to get a head-start on me. 

Best regards my friends. 
Noah B. 

PS: My personal experience with OpenCV was specifically dealing with automated 
turrets. There are great YouTube examples of using OpenCV for face-tracking 
webcams attached to servos, and blob isolating security cameras if you wanted 
specific examples to look up. 

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