noRANSAC for fundamental matrix estimation

Risultato della ricerca: Conference contribution

5 Citazioni (Scopus)

Abstract

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
Lingua originaleEnglish
Titolo della pubblicazione ospiteProceedings of 22th British Machine Vision Conference, BMVC 2011
Pagine1-11
Numero di pagine11
Stato di pubblicazionePublished - 2011

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All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition

Cita questo

Tegolo, D., & Bellavia, F. (2011). noRANSAC for fundamental matrix estimation. In Proceedings of 22th British Machine Vision Conference, BMVC 2011 (pagg. 1-11)