Abstract
In this paper we present a novel variational model to jointly estimate geometry and motion from a sequence of light fields captured with a plenoptic camera. The proposed model uses the so-called sub-aperture representation of the light field. Sub-aperture images represent images with slightly different viewpoints, which can be extracted from the light field. The sub-aperture representation allows us to formulate a convex global energy functional, which enforces multi-view geometry consistency, and piecewise smoothness assumptions on the scene flow variables. We optimize the proposed scene flow model by using an efficient preconditioned primal-dual algorithm. Finally, we also present synthetic and real world experiments.
Originalsprache | englisch |
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Titel | Pattern Recognition: 36th German Conference, GCPR 2014, M{\"u}nster, Germany, September 2-5, 2014, Proceedings |
Herausgeber (Verlag) | Springer International Publishing AG |
Seiten | 3-14 |
Band | 8753 |
ISBN (elektronisch) | 978-3-319-11752-2 |
ISBN (Print) | 978-3-319-11751-5 |
DOIs | |
Publikationsstatus | Angenommen/In Druck - 2014 |
Fields of Expertise
- Information, Communication & Computing