Automatic photo pop-up

Derek Hoiem, Alexei A. Efros, Martial Hebert

Research output: Contribution to journalConference article

Abstract

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.

Original languageEnglish (US)
Pages (from-to)577-584
Number of pages8
JournalACM Transactions on Graphics
Volume24
Issue number3
DOIs
StatePublished - Jul 1 2005
EventACM SIGGRAPH 2005 - Los Angeles, CA, United States
Duration: Jul 31 2005Aug 4 2005

Keywords

  • Image segmentation
  • Image-based rendering
  • Machine learning
  • Single-view reconstruction

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design

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