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Model Selection for Two View Geometry:A Review

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Shape, Contour and Grouping in Computer Vision

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1681))

Abstract

Computer vision often involves the estimation of models of the world from visual input. Sometimes it is possible to fit several dif- ferent models or hypotheses to a set of data, the choice of exactly which model is usually left to the vision practitioner. This paper explores ways of automating the model selection process, with specific emphasis on the least squares problem, and the handling of implicit or nuisance parame- ters (which in this case equate to 3D structure). The statistical literature is reviewed and it will become apparent that although no one method has yet been developed that will be generally useful for all computer vi- sion problems, there do exist some useful partial solutions. This paper is intended as a pragmatic beginner’s guide to model selection, highlighting the pertinent problems and illustrating them using two view geometry determination.

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  1. Microsoft Research One Microsoft Way, Redmond, WA, 98052, USA

    Philip H. S. Torr

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  1. Philip H. S. Torr
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© 1999 Springer-Verlag Berlin Heidelberg

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Torr, P.H.S. (1999). Model Selection for Two View Geometry:A Review. In: Shape, Contour and Grouping in Computer Vision. Lecture Notes in Computer Science, vol 1681. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46805-6_17

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  • DOI: https://doi.org/10.1007/3-540-46805-6_17

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  • Print ISBN: 978-3-540-66722-3

  • Online ISBN: 978-3-540-46805-9

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