The Robotics Institute

Carnegie Mellon Robotics Institute

Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.

Abstract

Occlusion reasoning, necessary for tasks such as navigation and object search, is an important aspect of everyday life and a fundamental problem in computer vision. We believe that the amazing ability of humans to reason about occlusions from one image is based on an intrinsically 3D interpretation. In this paper, our goal is to recover the occlusion boundaries and depth ordering of free-standing structures in the scene. Our approach is to learn to identify and label occlusion boundaries using the traditional edge and region cues together with 3D surface and depth cues. Since some of these cues require good spatial support (i.e., a segmentation), we gradually create larger regions and use them to improve inference over the boundaries. Our experiments demonstrate the power of a scene-based approach to occlusion reasoning.

Notes

Associated Project(s): Geometrically Coherent Image Interpretation

Number of pages: 8

Text Reference

Derek Hoiem, Andrew Stein, Alexei A. Efros, and Martial Hebert, "Recovering Occlusion Boundaries from a Single Image," International Conference on Computer Vision (ICCV), October, 2007.

BibTeX Reference

@inproceedings{Hoiem_2007_5826,
   author = "Derek Hoiem and Andrew Stein and Alexei A. Efros and Martial Hebert",
   title = "Recovering Occlusion Boundaries from a Single Image",
   booktitle = "International Conference on Computer Vision (ICCV)",
   month = "October",
   year = "2007",
}

The Robotics Institute

Menu