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Statements

Subject Item
n2:RIV%2F00216305%3A26230%2F07%3APU70857%21RIV08-MSM-26230___
rdf:type
n11:Vysledek skos:Concept
dcterms:description
The paper deals with a solution for visual surveillance metadata management. Data coming from many cameras is annotated using computer vision units to produce metadata representing moving objects in their states. It is assumed that the data is often uncertain, noisy and some states are missing. <p>The solution consists of the following three layers: (a) data cleaning layer - improves quality of the data by smoothing it and by filling in missing states in short sequences referred to as tracks that represent a composite state of a moving object in a spatiotemporal subspace followed by one camera. (b) Data integration layer - assigns a global identity to tracks that represent the same object. (c) Persistence layer - manages the metadata in a database so that it can be used for online identification and offline querying, analyzing and mining. A Kalman filter technique is used to solve (a) and a classification based on the moving object's state and its visual properties is used in (b). An object model for The paper deals with a solution for visual surveillance metadata management. Data coming from many cameras is annotated using computer vision units to produce metadata representing moving objects in their states. It is assumed that the data is often uncertain, noisy and some states are missing. <p>The solution consists of the following three layers: (a) data cleaning layer - improves quality of the data by smoothing it and by filling in missing states in short sequences referred to as tracks that represent a composite state of a moving object in a spatiotemporal subspace followed by one camera. (b) Data integration layer - assigns a global identity to tracks that represent the same object. (c) Persistence layer - manages the metadata in a database so that it can be used for online identification and offline querying, analyzing and mining. A Kalman filter technique is used to solve (a) and a classification based on the moving object's state and its visual properties is used in (b). An object model for Článek se zabývá řešením správy metadat pro vizuální dohled. Data přicházející z mnoha kamer jsou anotována pomocí jednotek počítačového vidění, které produkují metadata reprezentující pohybující objekty v jejich stavech. Předpokládáme, že data jsou nespolehlivá, zašuměná a některé stavy chybějí.<br> Řešení spočívá ve třech vrstvách: (a) čištění dat - zvyšuje jejich kvalitu (pomocí Kalmanova filtu), (b) integrace - přiřazuje pohybujícím se objektům globální identifikátor (Bayesovká klasifikace, SVM), (c) persistentní vrstva zajišťuje správu metadat, dotazování v reálném čase, analýzu dat a umožňuje dolování.<br> <br>
dcterms:title
Visual Surveillance Metadata Management Správa metadat pro vizuální dohled Visual Surveillance Metadata Management
skos:prefLabel
Správa metadat pro vizuální dohled Visual Surveillance Metadata Management Visual Surveillance Metadata Management
skos:notation
RIV/00216305:26230/07:PU70857!RIV08-MSM-26230___
n4:strany
79-83
n4:aktivita
n7:Z
n4:aktivity
Z(MSM0021630528)
n4:dodaniDat
n6:2008
n4:domaciTvurceVysledku
n15:4652738 n15:3725340
n4:druhVysledku
n19:D
n4:duvernostUdaju
n12:S
n4:entitaPredkladatele
n10:predkladatel
n4:idSjednocenehoVysledku
458027
n4:idVysledku
RIV/00216305:26230/07:PU70857
n4:jazykVysledku
n16:eng
n4:klicovaSlova
Visual surveillance, metadata management, cameras, vision units, moving objects, data cleaning, integration, persistence, Kalman filter, classification, object model.
n4:klicoveSlovo
n13:vision%20units n13:data%20cleaning n13:Kalman%20filter n13:moving%20objects n13:cameras n13:object%20model. n13:integration n13:metadata%20management n13:persistence n13:classification n13:Visual%20surveillance
n4:kontrolniKodProRIV
[EA4552812915]
n4:mistoKonaniAkce
Regensburg
n4:mistoVydani
Regensburg
n4:nazevZdroje
Eighteenth International Workshop on Database and Expert Systems Applications
n4:obor
n18:JC
n4:pocetDomacichTvurcuVysledku
2
n4:pocetTvurcuVysledku
2
n4:rokUplatneniVysledku
n6:2007
n4:tvurceVysledku
Zendulka, Jaroslav Chmelař, Petr
n4:typAkce
n5:WRD
n4:zahajeniAkce
2007-09-03+02:00
n4:zamer
n8:MSM0021630528
s:numberOfPages
5
n21:hasPublisher
IEEE Computer Society Press
n14:isbn
978-0-7695-2932-5
n20:organizacniJednotka
26230