Automatic implementation of the numerical Taylor series method: A Mathematica and Sage approach
Resumen: This paper presents a dense monocular mapping algorithm that improves the accuracy of the state-of-the-art variational and multiview stereo methods by incorporat- ing scene priors into its formulation. Most of the improvement of our proposal is in low- textured image regions and for low-parallax camera motions; two typical failure cases of multiview mapping.
The specific priors we model are the pla- narity of homogeneous color regions, the re- peating geometric primitives of the scene –that can be learned from data– and the Manhat- tan structure of indoor rooms. We evaluate the performance of our method in our own sequences and in the publicly available NYU dataset, emphasizing its strengths and weak- nesses in different cases.

Idioma: Inglés
DOI: 10.1016/j.amc.2015.06.042
Año: 2015
Publicado en: Applied Mathematics and Computation 268 (2015), 227-245
ISSN: 0096-3003

Factor impacto JCR: 1.345 (2015)
Categ. JCR: MATHEMATICS, APPLIED rank: 54 / 254 = 0.213 (2015) - Q1 - T1
Factor impacto SCIMAGO: 0.95 - Computational Mathematics (Q2) - Applied Mathematics (Q2)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2012-32100
Financiación: info:eu-repo/grantAgreement/ES/MINECO/DPI2012-32168
Financiación: info:eu-repo/grantAgreement/ES/MINECO/IPT2012-1309-430000
Tipo y forma: Article (PostPrint)
Área (Departamento): Área Matemática Aplicada (Dpto. Matemática Aplicada)
Área (Departamento): Área Física de la Tierra (Dpto. Física Teórica)
Área (Departamento): Área Didáctica Matemática (Dpto. Matemáticas)

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