Estimating Spatial Layout of Rooms using Volumetric Reasoning about Objects and Surfaces

Part of Advances in Neural Information Processing Systems 23 (NIPS 2010)

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Abhinav Gupta, Martial Hebert, Takeo Kanade, David Blei


There has been a recent push in extraction of 3D spatial layout of scenes. However, none of these approaches model the 3D interaction between objects and the spatial layout. In this paper, we argue for a parametric representation of objects in 3D, which allows us to incorporate volumetric constraints of the physical world. We show that augmenting current structured prediction techniques with volumetric reasoning significantly improves the performance of the state-of-the-art.