### Abstract

Lingua originale | English |
---|---|

Titolo della pubblicazione ospite | Proceedings of 22th British Machine Vision Conference, BMVC 2011 |

Pagine | 1-11 |

Numero di pagine | 11 |

Stato di pubblicazione | Published - 2011 |

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### All Science Journal Classification (ASJC) codes

- Computer Vision and Pattern Recognition

### Cita questo

*Proceedings of 22th British Machine Vision Conference, BMVC 2011*(pagg. 1-11)

**noRANSAC for fundamental matrix estimation.** / Tegolo, Domenico; Bellavia, Fabio.

Risultato della ricerca: Conference contribution

*Proceedings of 22th British Machine Vision Conference, BMVC 2011.*pagg. 1-11.

}

TY - GEN

T1 - noRANSAC for fundamental matrix estimation

AU - Tegolo, Domenico

AU - Bellavia, Fabio

PY - 2011

Y1 - 2011

N2 - The estimation of the fundamental matrix from a set of corresponding points is a relevant topic in epipolar stereo geometry [10]. Due to the high amount of outliers between the matches, RANSAC-based approaches [7, 13, 29] have been used to obtain the fundamental matrix. In this paper two new contributes are presented: a new normalized epipolar error measure which takes into account the shape of the features used as matches [17] and a new strategy to compare fundamental matrices. The proposed error measure gives good results and it does not depend on the image scale. Moreover, the new evaluation strategy describes a valid tool to compare different RANSAC-based methods because it does not rely on the inlier ratio, which could not correspond to the best allowable fundamental matrix estimated model, but it makes use of a reference ground truth fundamental matrix obtained by a set of corresponding points given by the user

AB - The estimation of the fundamental matrix from a set of corresponding points is a relevant topic in epipolar stereo geometry [10]. Due to the high amount of outliers between the matches, RANSAC-based approaches [7, 13, 29] have been used to obtain the fundamental matrix. In this paper two new contributes are presented: a new normalized epipolar error measure which takes into account the shape of the features used as matches [17] and a new strategy to compare fundamental matrices. The proposed error measure gives good results and it does not depend on the image scale. Moreover, the new evaluation strategy describes a valid tool to compare different RANSAC-based methods because it does not rely on the inlier ratio, which could not correspond to the best allowable fundamental matrix estimated model, but it makes use of a reference ground truth fundamental matrix obtained by a set of corresponding points given by the user

UR - http://hdl.handle.net/10447/60416

UR - http://www.bmva.org/bmvc/2011/proceedings/paper98/index.html

M3 - Conference contribution

SN - 1-901725-43-X

SP - 1

EP - 11

BT - Proceedings of 22th British Machine Vision Conference, BMVC 2011

ER -