Surface normal integration for convex space-time multi-view reconstruction
Oswald MR, Cremers D (2014)
Publication Type: Conference contribution
Publication year: 2014
Publisher: British Machine Vision Association, BMVA
Conference Proceedings Title: BMVC 2014 - Proceedings of the British Machine Vision Conference 2014
Event location: Nottingham, GBR
DOI: 10.5244/c.28.58
Abstract
We show that surface normal information allows to significantly improve the accuracy of a spatio-temporal multi-view reconstruction. On one hand, normal information can improve the quality of photometric matching scores. On the other hand, the same normal information can be employed to drive an adaptive anisotropic surface regularization process which better preserves fine details and elongated structures than its isotropic counterpart. We demonstrate how normal information can be used and estimated and explain crucial steps for an efficient implementation. Experiments on several challenging multi-view video data sets show clear improvements over state-of-the-art methods.
Involved external institutions
Germany (DE)How to cite
APA:
Oswald, M.R., & Cremers, D. (2014). Surface normal integration for convex space-time multi-view reconstruction. In Michel Valstar, Andrew French, Tony Pridmore (Eds.), BMVC 2014 - Proceedings of the British Machine Vision Conference 2014. Nottingham, GBR: British Machine Vision Association, BMVA.
MLA:
Oswald, Martin R., and Daniel Cremers. "Surface normal integration for convex space-time multi-view reconstruction." Proceedings of the 25th British Machine Vision Conference, BMVC 2014, Nottingham, GBR Ed. Michel Valstar, Andrew French, Tony Pridmore, British Machine Vision Association, BMVA, 2014.
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