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Automatic photo pop-up
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DOI：10.1145/1073204.1073232.png)
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摘要
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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.
Keyword:
image-based rendering
single-view reconstruction
machine learning
image segmentation
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9.5
论文数:
4.7K
被引数:
3.6W
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