Automatic photo pop-up

被引:390
作者
Hoiem, D [1 ]
Efros, AA [1 ]
Hebert, M [1 ]
机构
[1] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
来源
ACM TRANSACTIONS ON GRAPHICS | 2005年 / 24卷 / 03期
关键词
image-based rendering; single-view reconstruction; machine learning; image segmentation;
D O I
10.1145/1073204.1073232
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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 album.
引用
收藏
页码:577 / 584
页数:8
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