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Multi-View Matching Tensors from Lines for General Camera Models

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Tensors in Image Processing and Computer Vision

Part of the book series: Advances in Pattern Recognition ((ACVPR))

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Abstract

General camera models relax the constraint on central projection and characterize cameras as mappings between each pixel and the corresponding projection rays. This allows to describe most cameras types, including classical pinhole cameras, cameras with various optical distortions, catadioptric cameras and other acquisition devices. We deal with the structure from motion problem for such general models. We first consider an hierarchy of general cameras first introduced in [28] where the cameras are described according to the number of points and lines that have a non-empty intersection with all the projection rays. Then we propose a study of the multi-view geometry of such cameras and a new formulation of multi-view matching tensors working for projection rays crossing the same 3D line, the counterpart of the fundamental matrices and the multifocal tensors of the standard perspective cameras. We also delineate a method to estimate such tensors and recover the motion between the views.

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Authors and Affiliations

  1. INRIA Grenoble–Rhône-Alpes, 38334 Montbonnot St. Martin, France

    Simone Gasparini & Peter Sturm

Authors
  1. Simone Gasparini
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  2. Peter Sturm
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Correspondence to Simone Gasparini .

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Editors and Affiliations

  1. Escuela Técnica Superior de Ingenieros de Telecomunicacíon, Universidad de Valladolid, Campus Miguel Delibes, 47011 Valladolid, Spain

    Santiago Aja-Fernández  & Rodrigo de Luis García  & 

  2. Dept. Computing, HongKong Polytechnic University, Hong Kong

    Dacheng Tao

  3. University of London Birkbeck College School of Computer Science & Information Systems, Malet Street, London, WC1E 7HX, UK

    Xuelong Li

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© 2009 Springer-Verlag London Limited

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Gasparini, S., Sturm, P. (2009). Multi-View Matching Tensors from Lines for General Camera Models. In: Aja-Fernández, S., de Luis García, R., Tao, D., Li, X. (eds) Tensors in Image Processing and Computer Vision. Advances in Pattern Recognition. Springer, London. https://doi.org/10.1007/978-1-84882-299-3_9

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  • DOI: https://doi.org/10.1007/978-1-84882-299-3_9

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84882-298-6

  • Online ISBN: 978-1-84882-299-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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