We introduce an approach for analyzing annotated maps of a site, together with Internet photos, to reconstruct large indoor spaces of famous tourist sites. While current 3D reconstruction algorithms often produce a set of disconnected components (3D pieces) for indoor scenes due to scene coverage or matching failures, we make use of a provided map to lay out the 3D pieces in a global coordinate system. Our approach leverages position, orientation, and shape cues extracted from the map and 3D pieces and optimizes a global objective to recover the global layout of the pieces. We introduce a novel crowd flow cue that measures how people move across the site to recover 3D geometry orientation. We show compelling results on major tourist sites.
The research was supported in part by the National Science Foundation (IIS-1250793), the Intel Science and Technology Center for Visual Computing (ISTC-VC), the Animation Research Labs, and Google.