| dc.contributor.author | Farenzena, Michela | en_US |
| dc.contributor.author | Fusiello, Andrea | en_US |
| dc.contributor.editor | Mike Chantler | en_US |
| dc.date.accessioned | 2016-02-11T13:30:55Z | |
| dc.date.available | 2016-02-11T13:30:55Z | |
| dc.date.issued | 2005 | en_US |
| dc.identifier.isbn | 3-905673-57-6 | en_US |
| dc.identifier.uri | http://dx.doi.org/10.2312/vvg.20051013 | en_US |
| dc.description.abstract | In 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.publisher | The Eurographics Association | en_US |
| dc.title | Rigorous Computing in Computer Vision | en_US |
| dc.description.seriesinformation | Vision, Video, and Graphics (2005) | en_US |
| dc.description.sectionheaders | Motion, Synthesis and Computational Methods | en_US |
| dc.identifier.doi | 10.2312/vvg.20051013 | en_US |
| dc.identifier.pages | 101-108 | en_US |
