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This paper addresses the problem of Structure from Motion (SfM) for indoorpanoramic image streams, extremely challenging even for the state-of-the-artdue to the lack of textures and minimal parallax. The key idea is the fusion ofsingle-view and multi-view reconstruction techniques via geometric relationshipdetection (e.g., detecting 2D lines as coplanar in 3D). Rough geometry sufficesto perform such detection, and our approach utilizes rough surface normalestimates from an image-to-normal deep network to discover geometricrelationships among lines. The detected relationships provide exact geometricconstraints in our line-based linear SfM formulation. A constrained linearleast squares is used to reconstruct a 3D model and camera motions, followed bythe bundle adjustment. We have validated our algorithm on challenging datasets,outperforming various state-of-the-art reconstruction techniques.

Panoramic Structure from Motion via Geometric Relationship Detection