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Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F13%3A10173926%21RIV14-GA0-11320___
rdf:type
n16:Vysledek skos:Concept
rdfs:seeAlso
http://www.sciencedirect.com/science/article/pii/S1877050913010491
dcterms:description
Current popularity of augmented reality (AR) stems from its ability to enhance the perceived environment in real-time with additional information of semantic context, such as sports scores shown on TV during match broadcasting. Its other application areas range from industry and medicine to military, commerce and entertainment. Advanced AR technologies obviously rely on accurate, yet fast enough algorithms for multimedia processing and object recognition. In this paper, we study the possibility of using convolutional neural networks for real-time detection of hockey players from videos of broadcasted ice-hockey matches. Current popularity of augmented reality (AR) stems from its ability to enhance the perceived environment in real-time with additional information of semantic context, such as sports scores shown on TV during match broadcasting. Its other application areas range from industry and medicine to military, commerce and entertainment. Advanced AR technologies obviously rely on accurate, yet fast enough algorithms for multimedia processing and object recognition. In this paper, we study the possibility of using convolutional neural networks for real-time detection of hockey players from videos of broadcasted ice-hockey matches.
dcterms:title
Fast and Reliable Detection of Hockey Players Fast and Reliable Detection of Hockey Players
skos:prefLabel
Fast and Reliable Detection of Hockey Players Fast and Reliable Detection of Hockey Players
skos:notation
RIV/00216208:11320/13:10173926!RIV14-GA0-11320___
n16:predkladatel
n17:orjk%3A11320
n3:aktivita
n21:P
n3:aktivity
P(GAP103/10/0783), P(GAP202/10/1333)
n3:cisloPeriodika
20
n3:dodaniDat
n8:2014
n3:domaciTvurceVysledku
n11:9855890 n11:6046797
n3:druhVysledku
n18:J
n3:duvernostUdaju
n15:S
n3:entitaPredkladatele
n20:predkladatel
n3:idSjednocenehoVysledku
74695
n3:idVysledku
RIV/00216208:11320/13:10173926
n3:jazykVysledku
n4:eng
n3:klicovaSlova
k-means clustering; generalization; convolutional neural networks; image classification; augmented reality
n3:klicoveSlovo
n6:generalization n6:convolutional%20neural%20networks n6:image%20classification n6:k-means%20clustering n6:augmented%20reality
n3:kodStatuVydavatele
NL - Nizozemsko
n3:kontrolniKodProRIV
[EDBA183B8201]
n3:nazevZdroje
Procedia Computer Science
n3:obor
n10:BD
n3:pocetDomacichTvurcuVysledku
2
n3:pocetTvurcuVysledku
2
n3:projekt
n12:GAP103%2F10%2F0783 n12:GAP202%2F10%2F1333
n3:rokUplatneniVysledku
n8:2013
n3:svazekPeriodika
2013
n3:tvurceVysledku
Mrázová, Iveta Hrinčár, Matej
s:issn
1877-0509
s:numberOfPages
7
n19:doi
10.1016/j.procs.2013.09.249
n13:organizacniJednotka
11320