Hi Ben et al
I have been thinking about the vision problem, it seems that the model-based approach is most promising. After studying a lot of real digital pics, I have confidence that, with this approach, a vision system can be developed that can recognize almost everything humans can (with proper training of course).
I think the appropriate interface between the vision module and the AGI would be a "physical world model" (PWM). Such a model is composed of objects which are in turn composed of geons*. The PWM contains knowledge about physical objects, for example the fact that a TV is usually a "block", with a slightly concave screen, and some buttons which are small cubes/cylinders. Well, an old-fashioned TV. Or, a bottle is usually a cylinder with an empty "inside", and is topologically isomorphic with many other types of containers.
I don't know if Novamente currently has such a PWM (perhaps by another name). Anyway, my vision module has to interact with the PWM. The main function of the vision module is to map the geon-based model to
appearances. I've had this part roughly figured out.
Novamente's part is to help construct such a world model. We need to find out how to represent objects, geons (which I can handle), and the interrelations between objects. Let's avoid doing overlapping work...
Let's discuss this here to flesh out the details. That would speed things up a lot. Then I'll put everything on a web site. If I have time I'll do a presentation, but I think a paper is most important.
*geons: by this I mean a set of geometric primitives more general than the shapes commonly defined as geons in the literature. My geons are like partial "motifs" that can compose objects -- slightly lower-level than common geons.
yky
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