A convex solution to spatially-regularized correspondence problems
Windheuser T, Cremers D (2016)
Publication Type: Conference contribution
Publication year: 2016
Journal
Publisher: Springer Verlag
Book Volume: 9906 LNCS
Pages Range: 853-868
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Amsterdam, NLD
ISBN: 9783319464749
DOI: 10.1007/978-3-319-46475-6_52
Abstract
We propose a convex formulation of the correspondence problem between two images with respect to an energy function measuring data consistency and spatial regularity. To this end, we formulate the general correspondence problem as the search for a minimal twodimensional surface in ℝ4.We then use tools from geometric measure theory and introduce 2-vector fields as a representation of two-dimensional surfaces in ℝ4. We propose a discretization of this surface formulation that gives rise to a convex minimization problem and compute a globally optimal solution using an efficient primal-dual algorithm.
Involved external institutions
Germany (DE)How to cite
APA:
Windheuser, T., & Cremers, D. (2016). A convex solution to spatially-regularized correspondence problems. In Bastian Leibe, Nicu Sebe, Max Welling, Jiri Matas (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 853-868). Amsterdam, NLD: Springer Verlag.
MLA:
Windheuser, Thomas, and Daniel Cremers. "A convex solution to spatially-regularized correspondence problems." Proceedings of the 14th European Conference on Computer Vision, ECCV 2016, Amsterdam, NLD Ed. Bastian Leibe, Nicu Sebe, Max Welling, Jiri Matas, Springer Verlag, 2016. 853-868.
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