State-of-the-art in Visual Geo-localization
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F17%3APU123185" target="_blank" >RIV/00216305:26230/17:PU123185 - isvavai.cz</a>
Result on the web
<a href="http://cadik.posvete.cz/papers/brejcha-cadik17geolocalization_methods_survey.pdf" target="_blank" >http://cadik.posvete.cz/papers/brejcha-cadik17geolocalization_methods_survey.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/s10044-017-0611-1" target="_blank" >10.1007/s10044-017-0611-1</a>
Alternative languages
Result language
angličtina
Original language name
State-of-the-art in Visual Geo-localization
Original language description
Large-scale visual geo-localization has recently gained a lot of attention in computer vision research and new methods are proposed steadily. However, surveys of visual geo-localization methods are rare and they focus mainly on city-scale localization methods. We present a comprehensive and balanced study of existing visual geo-localization domains, including city-scale, global approaches and methods for natural environments. We overview the methods to show their pros and cons, application domains, datasets, as well as evaluation techniques. We categorize the reviewed methods by two criteria. The first is the type of data the method uses for geo-location estimation. The second criterion is the target environment for which the method has been proposed and validated. Based on this categorization we analyze important conditions that must be considered while solving geo-localization problems. Each category is in a different state of research - while city-scale image-based methods received a lot of attention, other categories like natural environments using cross-domain data sources are still challenging problems under active research. Future research of large-scale visual geo-localization is discussed, primarily the challenging and new research category - geo-localization in natural environments.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
PATTERN ANALYSIS AND APPLICATIONS
ISSN
1433-7541
e-ISSN
1433-755X
Volume of the periodical
2017
Issue of the periodical within the volume
3
Country of publishing house
GB - UNITED KINGDOM
Number of pages
25
Pages from-to
1-25
UT code for WoS article
000405607000001
EID of the result in the Scopus database
2-s2.0-85016120066