| Bilinear Modelling via Augmented Lagrange Multipliers (BALM). | |
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MedLine Citation:
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PMID: 22156102 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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This paper presents a unified approach to solve different bilinear factorization problems in computer vision in the presence of missing data in the measurements. The problem is formulated as a constrained optimization where one of the factors must lie on a specific manifold. To achieve this, we introduce an equivalent reformulation of the bilinear factorization problem that decouples the core bilinear aspect from the manifold specificity. We then tackle the resulting constrained optimization problem via Augmented Lagrange Multipliers. The strength and the novelty of our approach is that this framework can handle seamlessly different computer vision problems. The algorithm is such that only a projector onto the manifold constraint is needed.We present experiments and results for some popular factorization problems in computer vision such as rigid, non-rigid and articulated Structure from Motion; photometric stereo and 2D-3D non-rigid registration. |
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Authors:
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Alessio Del Bue; Joao Xavier; Lourdes Agapito; Marco Paladini |
Publication Detail:
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Type: JOURNAL ARTICLE Date: 2011-12-7 |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: - ISSN: 1939-3539 ISO Abbreviation: - Publication Date: 2011 Dec |
Date Detail:
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Created Date: 2011-12-13 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Affiliation:
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Istituto Italiano di Tecnologia, Genova. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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