journal contribution posted on 01.01.2005, 00:00 by Derek Hoiem, Alexei A Efros, Martial Hebert
This paper presents a fully automatic method for creating a 3D
model from a single photograph. The model is made up of several
texture-mapped planar billboards and has the complexity of a
typical children’s pop-up book illustration. Our main insight is that
instead of attempting to recover precise geometry, we statistically
model geometric classes defined by their orientations in the scene.
Our algorithm labels regions of the input image into coarse categories:
“ground”, “sky”, and “vertical”. These labels are then used
to “cut and fold” the image into a pop-up model using a set of simple
assumptions. Because of the inherent ambiguity of the problem
and the statistical nature of the approach, the algorithm is not expected
to work on every image. However, it performs surprisingly
well for a wide range of scenes taken from a typical person’s photo
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© ACM, 2005. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in the International Conference on Computer Graphics and Interactive Techniques (2005).