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Recovering the Spatial Layout of Cluttered Rooms


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 singleview 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.

Varsha Hedau, Derek Hoiem, David Forsyth, “Recovering the Spatial Layout of Cluttered Rooms,” in the Twelfth IEEE International Conference on Computer Vision, 2009.


Author = {Varsha Hedau and Derek Hoiem and David Forsyth},
Title = {Recovering the Spatial Layout of Cluttered Rooms},
Booktitle = {Proceedings of the {IEEE} International Conference on Computer Vision ({ICCV '09})},
Year = {2009},


Groundtruth data used in the above work. (314 Images 12 MB). ReadMe.txt

To obtain the code below, please email me at none


Computation of triplet of orthogonal vanishing points in an image, given detected straight line segments. This code is distributed as an executable compiled using matlab compiler.
Code] [ReadMe.txt] [MCRInstaller]

Spatial Layout Code:

Test code for estimating spatial layout of an image as described in ICCV'09 paper. Feature computation uses integral images in rectified domain, as described in ECCV'10. This is mainly done for speedup and might result into small differences in results. This package also contains source code for vanishing points executable provided above.
This code is distributed as is for research purpose only.
Code] [ReadMe.txt]

Demo code for free space estimation method described in ICCV'09 paper.