Rigorous Computing in Computer Vision

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dc.contributor.authorFarenzena, Michelaen_US
dc.contributor.authorFusiello, Andreaen_US
dc.contributor.editorMike Chantleren_US
dc.date.accessioned2016-02-11T13:30:55Z
dc.date.available2016-02-11T13:30:55Z
dc.date.issued2005en_US
dc.description.abstractIn this paper we discuss how Interval Analysis can be used to solve some problems in Computer Vision, namely autocalibration and triangulation. The crucial property of Interval Analysis is its ability to rigorously bound the range of a function over a given domain. This allows to propagate input errors with guaranteed results (used in multi-views triangulation) and to search for solution in non-linear minimisation problems with provably correct branch-and-bound algorithms (used in autocalibration). Experiments with real calibrated images illustrate the interval approach.en_US
dc.description.sectionheadersMotion, Synthesis and Computational Methodsen_US
dc.description.seriesinformationVision, Video, and Graphics (2005)en_US
dc.identifier.doi10.2312/vvg.20051013en_US
dc.identifier.isbn3-905673-57-6en_US
dc.identifier.pages101-108en_US
dc.identifier.urihttps://doi.org/10.2312/vvg.20051013en_US
dc.publisherThe Eurographics Associationen_US
dc.titleRigorous Computing in Computer Visionen_US
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