Inferring spatial layout from a single image via depth-ordered grouping

Inferring the 3D spatial layout from a single 2D image is a fundamental visual task. We formulate it as a grouping problem where edges are grouped into lines, quadrilaterals, and finally depth-ordered planes. We demonstrate that the 3D structure of planar objects in indoor scenes can be fast and accurately inferred without any learning or indexing.