Stanford's New Website Converts Your Photos to 3D
An anonymous reader writes to tell us that Stanford has a new website that not only shows you how cool their new 3-d modeling system is, but actually allows you to give it a try with your own photos. The system can take a 2-d still image and estimate a detailed 3-d structure which you can navigate. "For each small homogeneous patch in the image, we use a Markov Random Field (MRF) to infer a set of "plane parameters" that capture both the 3-d location and 3-d orientation of the patch. The MRF, trained via supervised learning, models both image depth cues as well as the relationships between different parts of the image. Other than assuming that the environment is made up of a number of small planes, our model makes no explicit assumptions about the structure of the scene; this enables the algorithm to capture much more detailed 3-d structure than does prior art (such as Saxena et al., 2005, Delage et al., 2005, and Hoiem et el., 2005), and also give a much richer experience in the 3-d flythroughs created using image-based rendering, even for scenes with significant non-vertical structure."
Wow, can you imagine how cool this would be with respect to video games? Drop in some photos, crank up the customized first person shooter, and zoooom! You could even take photos or shots from movies and do the same thing (e.g., using Star Wars stills).
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Could this type of technology be used for robots to allow them to identify what the 3d layout of the world around them is? Seems like a pretty powerful tool in that area.
granted, radar doesn't work so great for transparent surfaces to get the depth cue from -behind- that surface, while lidar gets a little iffy if it's -too- transparent to get the depth cue of that very surface. Combination of both - voila.
Several years ago I worked at a german university where recognizing of human faces was researched. We also did 3D reconstruction of faces, which was useful for training some algorithms. Although the technique is very different, 3D reconstruction from 2D images is not that new. Some examples can still be seen here: link
>> The server crashed after I gave it an image of the impossible triangle.
Actually - that one is really easy to do in 3D: http://autodesk.blogs.com/between_the_lines/2004/08/a_really_cool_3.html
Berkeley's already on it.
http://www-video.eecs.berkeley.edu/~frueh/3d/