This HTML5 document contains 40 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
n4http://linked.opendata.cz/ontology/domain/vavai/riv/typAkce/
n19http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216305%3A26220%2F11%3APU92370%21RIV11-MSM-26220___/
dctermshttp://purl.org/dc/terms/
n17http://purl.org/net/nknouf/ns/bibtex#
n6http://localhost/temp/predkladatel/
n12http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n15http://linked.opendata.cz/resource/domain/vavai/subjekt/
n14http://linked.opendata.cz/ontology/domain/vavai/
n9https://schema.org/
shttp://schema.org/
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n11http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n10http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n20http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n16http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n21http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n18http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n13http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216305%3A26220%2F11%3APU92370%21RIV11-MSM-26220___
rdf:type
skos:Concept n14:Vysledek
dcterms:description
This work introduces a complex method for real-time vehicle detection. It is based on analysis of video-sequence acquired from static camera situated on highway. Processing consists of many steps. It starts with a simple background subtraction and end with monitoring results, i.e. average speed, number of cars etc. This paper describes suitable approaches for solving single steps of analysis with respect to time requirements. This work introduces a complex method for real-time vehicle detection. It is based on analysis of video-sequence acquired from static camera situated on highway. Processing consists of many steps. It starts with a simple background subtraction and end with monitoring results, i.e. average speed, number of cars etc. This paper describes suitable approaches for solving single steps of analysis with respect to time requirements.
dcterms:title
Vehicle detection Vehicle detection
skos:prefLabel
Vehicle detection Vehicle detection
skos:notation
RIV/00216305:26220/11:PU92370!RIV11-MSM-26220___
n14:predkladatel
n15:orjk%3A26220
n3:aktivita
n16:S
n3:aktivity
S
n3:dodaniDat
n13:2011
n3:domaciTvurceVysledku
n12:6804411
n3:druhVysledku
n21:D
n3:duvernostUdaju
n10:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
238101
n3:idVysledku
RIV/00216305:26220/11:PU92370
n3:jazykVysledku
n20:eng
n3:klicovaSlova
vehicle detection, traffic monitoring, video analysis, segmentation
n3:klicoveSlovo
n11:vehicle%20detection n11:video%20analysis n11:segmentation n11:traffic%20monitoring
n3:kontrolniKodProRIV
[77EB130AE024]
n3:mistoKonaniAkce
Brno
n3:mistoVydani
Brno
n3:nazevZdroje
Proceedings of the 17th Conference STUDENT EEICT 2011
n3:obor
n18:JB
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
1
n3:rokUplatneniVysledku
n13:2011
n3:tvurceVysledku
Vomela, Miroslav
n3:typAkce
n4:CST
n3:zahajeniAkce
2011-04-28+02:00
s:numberOfPages
5
n17:hasPublisher
NOVPRESS s.r.o.
n9:isbn
978-80-214-4273-3
n6:organizacniJednotka
26220