Using line consistency to estimate 3D indoor Manhattan scene layout from a single image

In this paper, an optimization approach is proposed to estimate the 3D indoor Manhattan scene layout from a single input image. The proposed system models the interior space as a three-dimensional box which includes ceiling, floor, and walls. The regions corresponding to different surfaces can be calculated by projecting the 3D box onto the two-dimensional image with suitable camera and box parameters. This paper also utilizes the consistency of coplanar lines and the boundary edges between different surfaces to design a cost function. The rotation, translation, and box parameters of the interior layout can be estimated with an energy minimization process. In the experimental results, we apply the proposed algorithm to a number of real images of interior scenes to demonstrate the effectiveness of the proposed system.