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Holistic Scene Understanding
Stephen Gould,
Tianshi Gao,
Pawan Kumar,
Ben Packer,
Daphne Koller
Figure 1. Example Scene Decompositions with Semantic and Geometric Overlays.
Many works in computer vision attempt to tackle problems that form key
components in the scene interpretation task: object recognition, image
segmentation and 3D reconstruction. However, the vast majority of the
work has focused on solving each component in isolation. This approach
has allowed researchers to focus their efforts on engineering
solutions to each of these key problems, resulting in dramatic
improvements in our ability to tackle them. However, this
divide-and-conquer approach has two main limitations. First, because
there is no global understanding of the scene structure, many methods
make errors that appear ridiculous to a human, such as segmenting a
person's head as part of the background, or detecting a cow in the
shadows in the grass. Second, it is only by providing a consistent
set of answers to all of these problems that we can provide a coherent
interpretation for an entire scene. In this project, we develop an
integrated probabilistic model that provides a consistent, semantic
interpretation of all components of an outdoor scene.
Figure 2. Example 3D Geometric Reconstructions (click on image to play).
More coming soon...
related publications
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P. Kumar and D. Koller.
Efficiently Selecting Regions for Scene Understanding.
Proceedings of Conference on Computer Vision and Pattern Recognition (CVPR), 2010.
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S. Gould, T. Gao, D. Koller.
Region-based Segmentation and Object Detection.
Proceedings of Advances in Neural Information Processing Systems (NIPS), 2009.
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S. Gould, R. Fulton, D. Koller.
Decomposing a Scene into Geometric and Semantically Consistent Regions.
Proceedings of International Conference on Computer Vision (ICCV), 2009.
[pdf]
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G. Heitz, S. Gould, A. Saxena, D. Koller.
Cascaded Classification Models: Combining Models for Holistic Scene Understanding.
Proceedings of Advances in Neural Information Processing Systems (NIPS), 2008.
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datasets and other resources
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Stanford Background Dataset containing 715 images of outdoor
scenes from Gould et al. (ICCV 2009).
[.tar.gz | more]
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DAGS - Daphne's Approximate Group of Students. All rights reserved.