Skip to Main content Skip to Navigation
Conference papers

A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping Laws

Gilles Simon 1 Antoine Fond 1 Marie-Odile Berger 1
1 MAGRIT - Visual Augmentation of Complex Environments
Inria Nancy - Grand Est, LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry
Abstract : We show that, in images of man-made environments, the horizon line can usually be hypothesized based on a-contrario detections of second-order grouping events. This allows constraining the extraction of the horizontal vanishing points on that line, thus reducing false detections. Experiments made on three datasets show that our method, not only achieves state-of-the-art performance w.r.t. horizon line detection on two datasets, but also yields much less spurious vanishing points than the previous top-ranked methods.
Document type :
Conference papers
Complete list of metadata

Cited literature [17 references]  Display  Hide  Download

https://hal.inria.fr/hal-01865251
Contributor : Gilles Simon <>
Submitted on : Friday, August 31, 2018 - 11:14:54 AM
Last modification on : Tuesday, May 18, 2021 - 3:44:10 PM
Long-term archiving on: : Saturday, December 1, 2018 - 1:28:50 PM

File

1988.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-01865251, version 1

Collections

Citation

Gilles Simon, Antoine Fond, Marie-Odile Berger. A-Contrario Horizon-First Vanishing Point Detection Using Second-Order Grouping Laws. ECCV 2018 - European Conference on Computer Vision, Sep 2018, Munich, Germany. pp.323-338. ⟨hal-01865251⟩

Share

Metrics

Record views

540

Files downloads

832