Publication Details

Camera Elevation Estimation from a Single Mountain Landscape Photograph

ČADÍK, M.; VAŠÍČEK, J.; HRADIŠ, M.; RADENOVIĆ, F.; CHUM, O. Camera Elevation Estimation from a Single Mountain Landscape Photograph. In British Machine Vision Conference 2015. Swansea: The British Machine Vision Association and Society for Pattern Recognition, 2015. p. 1-12. ISBN: 978-1-901725-53-7.
Czech title
Odhad nadmořské výšky kamery z jediné fotografie přírodního prostředí
Type
conference paper
Language
English
Authors
Čadík Martin, doc. Ing., Ph.D. (DCGM)
Vašíček Jan, Ing.
Hradiš Michal, Ing., Ph.D. (DCGM)
Radenović Filip (FIT)
Chum Ondřej, doc. Mgr., Ph.D.
URL
Keywords

camera elevation, landscape mountain photographs dataset, cnn, neural networks, BOW

Abstract

This work addresses the problem of camera elevation estimation from a  single photograph in an outdoor environment. We introduce a new benchmark dataset of one-hundred thousand images with annotated camera elevation called Alps100K. We propose and experimentally evaluate two automatic data-driven approaches to camera elevation estimation: one based on convolutional neural networks, the other on local features. To compare the proposed methods to human performance, an experiment with 100 subjects is conducted. The experimental results show that both proposed approaches outperform humans and that the best result is achieved by their combination.

Annotation
Published
2015
Pages
1–12
Proceedings
British Machine Vision Conference 2015
ISBN
978-1-901725-53-7
Publisher
The British Machine Vision Association and Society for Pattern Recognition
Place
Swansea
DOI
EID Scopus
BibTeX
@inproceedings{BUT119883,
  author="Martin {Čadík} and Jan {Vašíček} and Michal {Hradiš} and Filip {Radenović} and Ondřej {Chum}",
  title="Camera Elevation Estimation from a Single Mountain Landscape Photograph",
  booktitle="British Machine Vision Conference 2015",
  year="2015",
  pages="1--12",
  publisher="The British Machine Vision Association and Society for Pattern Recognition",
  address="Swansea",
  doi="10.5244/C.29.30",
  isbn="978-1-901725-53-7",
  url="http://cphoto.fit.vutbr.cz/elevation/"
}
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