Learning to See Through Haze: Radar-based Human Detection for Adverse Weather Conditions
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F19%3A00334757" target="_blank" >RIV/68407700:21230/19:00334757 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8870954" target="_blank" >https://ieeexplore.ieee.org/document/8870954</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ECMR.2019.8870954" target="_blank" >10.1109/ECMR.2019.8870954</a>
Alternative languages
Result language
angličtina
Original language name
Learning to See Through Haze: Radar-based Human Detection for Adverse Weather Conditions
Original language description
In this paper, we present a lifelong-learning multisensor system for pedestrian detection in adverse weather conditions. The proposed method combines two people detection pipelines which process data provided by a lidar and an ultrawideband radar. The outputs of these pipelines are combined not only by means of adaptive sensor fusion, but they can also be used to help one another learn. In particular, the lidar-based detector provides labels to the incoming radar data, efficiently training the radar data classifier. In several experiments, we show that the proposed learning-fusion not only results in a gradual improvement of the system performance during routine operation, but also efficiently deals with lidar detection failures caused by thick fog conditions.
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
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
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 European Conference on Mobile Robots
ISBN
978-1-7281-3606-6
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
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Publisher name
Czech Technical University
Place of publication
Prague
Event location
Prague
Event date
Aug 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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