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Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F11%3APU96251%21RIV12-MSM-26220___
rdf:type
n8:Vysledek skos:Concept
dcterms:description
This paper addresses the problem of UGV navigation in various environments and lightning conditions. Previous approaches use a combination of different sensors, or work well, only in scenarios with noticeable road marking or borders. Our robot is used for chemical, nuclear and biological contamination measurement. Thus, to avoid complications with decontamination, only a monocular camera serves as a sensor since it is already equipped. In this paper, we propose a novel approach a fusion of frequency based vanishing point estimation and probabilistically based color segmentation. Detection of a vanishing point, is based on the estimation of a texture flow, produced by a bank of Gabor wavelets and a voting function. Next, the vanishing point defines the training area, which is used for self-supervised learning of color models. Finally, road patches are selected by measuring of the roadness score. A few rules deal with dark cast shadows, overexposed highlights and adaptivity speed. In addition to the rob This paper addresses the problem of UGV navigation in various environments and lightning conditions. Previous approaches use a combination of different sensors, or work well, only in scenarios with noticeable road marking or borders. Our robot is used for chemical, nuclear and biological contamination measurement. Thus, to avoid complications with decontamination, only a monocular camera serves as a sensor since it is already equipped. In this paper, we propose a novel approach a fusion of frequency based vanishing point estimation and probabilistically based color segmentation. Detection of a vanishing point, is based on the estimation of a texture flow, produced by a bank of Gabor wavelets and a voting function. Next, the vanishing point defines the training area, which is used for self-supervised learning of color models. Finally, road patches are selected by measuring of the roadness score. A few rules deal with dark cast shadows, overexposed highlights and adaptivity speed. In addition to the rob
dcterms:title
Robust detection of shady and highlighted roads for monocular camera based navigation of UGV Robust detection of shady and highlighted roads for monocular camera based navigation of UGV
skos:prefLabel
Robust detection of shady and highlighted roads for monocular camera based navigation of UGV Robust detection of shady and highlighted roads for monocular camera based navigation of UGV
skos:notation
RIV/00216305:26220/11:PU96251!RIV12-MSM-26220___
n8:predkladatel
n15:orjk%3A26220
n4:aktivita
n13:Z
n4:aktivity
Z(MSM0021630529)
n4:dodaniDat
n14:2012
n4:domaciTvurceVysledku
n5:3271064 n5:9821643 n5:3822761 n5:2980576
n4:druhVysledku
n22:D
n4:duvernostUdaju
n16:S
n4:entitaPredkladatele
n18:predkladatel
n4:idSjednocenehoVysledku
227301
n4:idVysledku
RIV/00216305:26220/11:PU96251
n4:jazykVysledku
n21:eng
n4:klicovaSlova
Adaptation models , Cameras , Estimation , Image color analysis , Roads , Robots , Training
n4:klicoveSlovo
n7:Roads%20 n7:Estimation%20 n7:Robots%20 n7:Cameras%20 n7:Adaptation%20models%20 n7:Training n7:Image%20color%20analysis%20
n4:kontrolniKodProRIV
[05BCE6F5F4F7]
n4:mistoKonaniAkce
Shanghai
n4:mistoVydani
Shanghai
n4:nazevZdroje
Proceedings of ICRA 2011
n4:obor
n17:JD
n4:pocetDomacichTvurcuVysledku
4
n4:pocetTvurcuVysledku
4
n4:rokUplatneniVysledku
n14:2011
n4:tvurceVysledku
Mikšík, Ondřej Jura, Pavel Petyovský, Petr Žalud, Luděk
n4:typAkce
n12:WRD
n4:zahajeniAkce
2011-05-09+02:00
n4:zamer
n20:MSM0021630529
s:numberOfPages
8
n9:hasPublisher
Neuveden
n6:isbn
978-1-61284-386-5
n19:organizacniJednotka
26220