Spatio-Semantic ConvNet-Based Visual Place Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337205" target="_blank" >RIV/68407700:21730/19:00337205 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1109/ECMR.2019.8870948" target="_blank" >https://doi.org/10.1109/ECMR.2019.8870948</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ECMR.2019.8870948" target="_blank" >10.1109/ECMR.2019.8870948</a>
Alternative languages
Result language
angličtina
Original language name
Spatio-Semantic ConvNet-Based Visual Place Recognition
Original language description
We present a Visual Place Recognition system that follows the two-stage format common to image retrieval pipelines. The system encodes images of places by employing the activations of different layers of a pre-trained, off-the-shelf, VGG16 Convolutional Neural Network (CNN) architecture. In the first stage of our method and given a query image of a place, a number of top candidate images is retrieved from a previously stored database of places. In the second stage, we propose an exhaustive comparison of the query image against these candidates by encoding semantic and spatial information in the form of CNN features. Results from our approach outperform by a large margin state-of-the-art visual place recognition methods on five of the most commonly used benchmark datasets. The performance gain is especially remarkable on the most challenging datasets, with more than a twofold recognition improvement with respect to the latest published work.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20204 - Robotics and automatic control
Result continuities
Project
<a href="/en/project/EF15_003%2F0000470" target="_blank" >EF15_003/0000470: Robotics 4 Industry 4.0</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2019 European Conference on Mobile Robots
ISBN
978-1-7281-3605-9
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
American Institute of Physics and Magnetic Society of the IEEE
Place of publication
San Francisco
Event location
Prague
Event date
Aug 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000558081900044