2008/8/14 Mike Tintner <[EMAIL PROTECTED]>: > What it comes down to is: what can you learn about any object[s] from flat > drawings of them? Cardboard cutouts?
This is essentially the same problem as in computer vision. The objects that you're looking at are three dimensional, but a camera image is only a two dimensional shadow of them. The problem then becomes one of trying to reverse engineer the 3D shape from a set of lower dimensional shadows. Many researchers in computational vision forget about this and try to directly scrape information exclusively in 2D. For objects which are flat, such as a painting or the cover of a book, this approach works well (see the vision systems from evolution robotics and skilligent) but on things which have significant 3D structure performance usually degrades significantly. ------------------------------------------- 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=111637683-c8fa51 Powered by Listbox: http://www.listbox.com
