Abstract
We introduce a novel framework for image-based 3D reconstruction of urban buildings based on symmetry priors. Starting from image-level edges, we generate a sparse and approximate set of consistent 3D lines. These lines are then used to simultaneously detect symmetric line arrangements while refining the estimated 3D model. Operating both on 2D image data and intermediate 3D feature representations, we perform iterative feature consolidation and effective outlier pruning, thus eliminating reconstruction artifacts arising from ambiguous or wrong stereo matches. We exploit non-local coherence of symmetric elements to generate precise model reconstructions, even in the presence of a significant amount of outlier image-edges arising from reflections, shadows, outlier objects, etc. We evaluate our algorithm on several challenging test scenarios, both synthetic and real. Beyond reconstruction, the extracted symmetry patterns are useful towards interactive and intuitive model manipulations.
Original language | English (US) |
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Pages (from-to) | 671-680 |
Number of pages | 10 |
Journal | Computer Graphics Forum |
Volume | 31 |
Issue number | 2pt3 |
DOIs | |
State | Published - Jun 20 2012 |
Bibliographical note
KAUST Repository Item: Exported on 2020-10-01Acknowledgements: This research has been supported by the ERC Starting Grant 257453 COSYM, a KAUST visiting student grant, and the Marie Curie Career Integration Grant 303541.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.