Published in Graphics

Stanford comes up with cool 3-D modeling


Image

But the server crashes


Stanford University
has been showing off rather cool 3-D modeling that takes a 2-D image and creates a navigable 3-D image.

According to the site, for each small homogeneous patch in the image, a Markov Random Field (MRF) is used to infer a set of "plane parameters" that capture both the 3-D location and 3-D orientation of the patch. The site said that the MRF, when trained, creates image depth cues as well as the relationships among different parts of the image.

It gives a much richer experience in the 3-D flythroughs created using image-based rendering, even for scenes with significant non-vertical structure. Stanford has set up a Web page that allowed people to upload a picture of their own and see how it worked. Unfortunately, it was spotted by Slashdot and interest was so high that the server crashed.

More here.
Last modified on 30 January 2008
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