Planar Structure Matching Under Projective Uncertainty for Geolocation
Abstract
Image based geolocation aims to answer the question: where was this ground photograph taken? We present an approach to geolocalating a single image based on matching human delineated line segments in the ground image to automatically detected line segments in ortho images. Our approach is based on distance transform matching. By observing that the uncertainty of line segments is non-linearly amplified by projective transformations, we develop an uncertainty based representation and incorporate it into a geometric matching framework. We show that our approach is able to rule out a considerable portion of false candidate regions even in a database composed of geographic areas with similar visual appearances.
Cite
Text
Li et al. "Planar Structure Matching Under Projective Uncertainty for Geolocation." European Conference on Computer Vision, 2014. doi:10.1007/978-3-319-10584-0_18Markdown
[Li et al. "Planar Structure Matching Under Projective Uncertainty for Geolocation." European Conference on Computer Vision, 2014.](https://mlanthology.org/eccv/2014/li2014eccv-planar/) doi:10.1007/978-3-319-10584-0_18BibTeX
@inproceedings{li2014eccv-planar,
title = {{Planar Structure Matching Under Projective Uncertainty for Geolocation}},
author = {Li, Ang and Morariu, Vlad I. and Davis, Larry S.},
booktitle = {European Conference on Computer Vision},
year = {2014},
pages = {265-280},
doi = {10.1007/978-3-319-10584-0_18},
url = {https://mlanthology.org/eccv/2014/li2014eccv-planar/}
}