This is absolutely incredible. The answer was right there in the last paragraph:
The present experiments suggest that the computation of object persistence appears to rely so heavily upon spatiotemporal information that it will not (or at least is unlikely to) use otherwise available surface feature information, particularly when there is conflicting spatiotemporal information. This reveals a striking limitation, given various theories that visual perception uses whatever shortcuts, or heuristics, it can to simplify processing, as well as the theory that perception evolves out of a buildup of the statistical nature of our environment (e.g., Purves & Lotto, 2003). Instead, it appears that the object file system has “tunnel vision” and turns a blind eye to surface feature information, focusing on spatiotemporal information when computing persistence. So much for Matt's claim that the brain uses hierarchical features!!!! LOL Dave On Sat, Jul 24, 2010 at 11:52 PM, David Jones <[email protected]> wrote: > Check this out! > > The title "Space and time, not surface features, guide object persistence" > says it all. > > http://pbr.psychonomic-journals.org/content/14/6/1199.full.pdf > > Over just the last couple days I have begun to realize that they are so > right. My idea before of using high frame rates is also spot on. The brain > does not use features as much as we think. First we construct a model of the > object, then we probably decide what features to index it with for future > search. If we know that the object occurs at a particular location in space, > then we can learn a great deal about it with very little ambiguity! Of > course, processing images at all is hard, but that's besides the point... > The point is that we can automatically learn about the world using high > frame rates and a simple heuristic for identifying specific objects in a > scene. Because we can reliably identify them, we can learn an extremely > large amount in a very short period of time. We can learn about how lighting > affects the colors, noise, size, shape, components, attachment > relationships, etc. etc. > > So, it is very likely that screenshots are not simpler than real images! > lol. The objects in real images usually don't change as much, as drastically > or as quickly as the objects in screenshots. That means that we can use the > simple heuristics of size, shape, location and continuity of time to match > objects and learn about them. > > Dave > > > On Sat, Jul 24, 2010 at 9:10 PM, Matt Mahoney <[email protected]>wrote: > >> Mike Tintner wrote: >> > Which is? >> >> The one right behind your eyes. >> >> >> -- Matt Mahoney, [email protected] >> >> >> ------------------------------ >> *From:* Mike Tintner <[email protected]> >> *To:* agi <[email protected]> >> *Sent:* Sat, July 24, 2010 9:00:42 PM >> >> *Subject:* Re: [agi] Re: Huge Progress on the Core of AGI >> >> Matt: >> I mean a neural model with increasingly complex features, as opposed to an >> algorithmic 3-D model (like video game graphics in reverse). Of course David >> rejects such ideas ( http://practicalai.org/Prize/Default.aspx ) even >> though the one proven working vision model uses it. >> >> >> Which is? and does what? (I'm starting to consider that vision and visual >> perception - or perhaps one should say "common sense", since no sense in >> humans works independent of the others - may well be considerably *more* >> complex than language. The evolutionary time required to develop our common >> sense perception and conception of the world was vastly greater than that >> required to develop language. And we are as a culture merely in our babbling >> infancy in beginning to understand how sensory images work and are >> processed). >> *agi* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/> | >> Modify<https://www.listbox.com/member/?&;>Your Subscription >> <http://www.listbox.com> >> *agi* | Archives <https://www.listbox.com/member/archive/303/=now> >> <https://www.listbox.com/member/archive/rss/303/> | >> Modify<https://www.listbox.com/member/?&;>Your Subscription >> <http://www.listbox.com> >> > > ------------------------------------------- agi Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/ Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=8660244-6e7fb59c Powered by Listbox: http://www.listbox.com
