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. © 2014 Springer International Publishing.
CITATION STYLE
Martin-Brualla, R., He, Y., Russell, B. C., & Seitz, S. M. (2014). The 3D jigsaw puzzle: Mapping large indoor spaces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8691 LNCS, pp. 1–16). Springer Verlag. https://doi.org/10.1007/978-3-319-10578-9_1
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