Optimal estimation of vanishing points in a Manhattan world

Faraz M. Mirzaei, Stergios I. Roumeliotis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

62 Scopus citations

Abstract

In this paper, we present an analytical method for computing the globally optimal estimates of orthogonal vanishing points in a "Manhattan world" with a calibrated camera. We formulate this as constrained least-squares problem whose optimality conditions form a multivariate polynomial system. We solve this system analytically to compute all the critical points of the least-squares cost function, and hence the global minimum, i.e., the globally optimal estimate for the orthogonal vanishing points. The same optimal estimator is used in conjunction with RANSAC to generate orthogonal-vanishing- point hypotheses (from triplets of lines) and thus classify lines into parallel and mutually orthogonal groups. The proposed method is validated experimentally on the York Urban Database.

Original languageEnglish (US)
Title of host publication2011 International Conference on Computer Vision, ICCV 2011
Pages2454-2461
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE International Conference on Computer Vision, ICCV 2011 - Barcelona, Spain
Duration: Nov 6 2011Nov 13 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision, ICCV 2011
Country/TerritorySpain
CityBarcelona
Period11/6/1111/13/11

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