@InProceedings{AraujoSamEvaManFer:2015:AcLoFa,
author = "Araujo, Andr{\'e} Alvarado and Sampaio, Jonas da Costa and
Evangelista, Raphael dos Santos and Mantuan, Altobelli de Brito
and Fernandes, Leandro Augusto Frata",
affiliation = "{Universidade Federal Fluminense (UFF)} and {Universidade Federal
Fluminense (UFF)} and {Universidade Federal Fluminense (UFF)} and
{Universidade Federal Fluminense (UFF)} and {Universidade Federal
Fluminense (UFF)}",
title = "Accurate location of fa{\c{c}}ades of interest in street view
panoramic sequences",
booktitle = "Proceedings...",
year = "2015",
editor = "Papa, Jo{\~a}o Paulo and Sander, Pedro Vieira and Marroquim,
Ricardo Guerra and Farrell, Ryan",
organization = "Conference on Graphics, Patterns and Images, 28. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "street view, geographical coordinates, environment map, feature
extraction, feature matching, error propagation.",
abstract = "Geo-spatial queries, i.e., queries that combine location data with
other kinds of input, have taken huge importance in the last
generation of search engines. The success of a geo-spatial search
depends on the quality of the positioning information provided,
for instance, by GPS-enabled smartphones. Therefore, the quality
of the GPS signal and the quality of the built-in GPS may affect
the accuracy of the estimated location, and hence the quality of
the searching result. This paper proposes an automatic image-based
solution for improving the estimation of the geographical
coordinates of a building of interest on which a geo-spatial
search will be performed. Our approach uses the inaccurate GPS
coordinates estimated by smartphones as starting point for
automated visual search into a graph of streets enhanced with
street view panoramic sequences. During the search, our approach
uses a query image of the building of interest to identify which
panoramic views include the building's fa{\c{c}}ade. From the
geographical location of the panoramic views and from the best
matching directions of the given image with the panoramic images,
our approach triangulates the location of the target building. In
addition, our approach estimates the uncertainty in the computed
locations by modeling the error propagation along the
triangulation procedure. We evaluate our method on several real
images of buildings.",
conference-location = "Salvador, BA, Brazil",
conference-year = "26-29 Aug. 2015",
doi = "10.1109/SIBGRAPI.2015.32",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2015.32",
language = "en",
ibi = "8JMKD3MGPBW34M/3JMJJ88",
url = "http://urlib.net/ibi/8JMKD3MGPBW34M/3JMJJ88",
targetfile = "PID3770445.pdf",
urlaccessdate = "2024, May 06"
}