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Recovering the spatial layout of cluttered rooms
Abstract
In this paper, we consider the problem of recovering the spatial layout of indoor scenes from monocular images. The presence of clutter is a major problem for existing single-view 3D reconstruction algorithms, most of which rely on finding the ground-wall boundary. In most rooms, this boundary is partially or entirely occluded. We gain robustness to clutter by modeling the global room space with a parameteric 3D “box” and by iteratively localizing clutter and refitting the box. To fit the box, we introduce a structured learning algorithm that chooses the set of parameters to minimize error, based on global perspective cues. On a dataset of 308 images, we demonstrate the ability of our algorithm to recover spatial layout in cluttered rooms and show several examples of estimated free space.
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Multiple View Geometry in Computer Vision
Hartley, R., & Zisserman, A. (2004) · doi:10.1017/cbo9780511811685 · Cited by 21,070
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Metadata
- Authors
- Hedau, V., Hoiem, D., & Forsyth, D.
- Venue
- 2009 IEEE 12th International Conference on Computer Vision
- Publisher
- IEEE
- Published
- 2009-09
- Pages
- 1849-1856
- OpenAlex
- W2534523274
- Cited by
- 487
- References
- 1
- FWCI
- 17.99
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Hedau, V., Hoiem, D., & Forsyth, D. (2009). Recovering the spatial layout of cluttered rooms. 2009 IEEE 12th International Conference on Computer Vision. https://doi.org/10.1109/iccv.2009.5459411
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