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Statements

Subject Item
n2:RIV%2F49777513%3A23520%2F10%3A00504550%21RIV11-GA0-23520___
rdf:type
n6:Vysledek skos:Concept
dcterms:description
In this paper we focus on the potential correlation of the manual and the non-manual component of sign language. This information is useful for sign language analysis, recognition and synthesis. We are mainly concerned with the application for sign synthesis. First we extracted features that represent the manual and non-manual component. We present a simple but robust method for the hand tracking to obtain a 2D trajectory representing a portion of the manual component. The head is tracked via Active Appearance Model. We introduce initial experiments to reveal the relationship between these features. The procedure is verified on the corpus of isolated signs from Czech Sign Language. The results imply that the components of sign language are correlated. The most correlated signals are the vertical movement of head and hands. In this paper we focus on the potential correlation of the manual and the non-manual component of sign language. This information is useful for sign language analysis, recognition and synthesis. We are mainly concerned with the application for sign synthesis. First we extracted features that represent the manual and non-manual component. We present a simple but robust method for the hand tracking to obtain a 2D trajectory representing a portion of the manual component. The head is tracked via Active Appearance Model. We introduce initial experiments to reveal the relationship between these features. The procedure is verified on the corpus of isolated signs from Czech Sign Language. The results imply that the components of sign language are correlated. The most correlated signals are the vertical movement of head and hands.
dcterms:title
Correlation analysis of facial features and sign gestures Correlation analysis of facial features and sign gestures
skos:prefLabel
Correlation analysis of facial features and sign gestures Correlation analysis of facial features and sign gestures
skos:notation
RIV/49777513:23520/10:00504550!RIV11-GA0-23520___
n3:aktivita
n13:S n13:P
n3:aktivity
P(GP102/09/P609), P(ME08106), S
n3:dodaniDat
n4:2011
n3:domaciTvurceVysledku
n12:9091424 n12:3572072 n12:4051351
n3:druhVysledku
n5:D
n3:duvernostUdaju
n17:S
n3:entitaPredkladatele
n16:predkladatel
n3:idSjednocenehoVysledku
252193
n3:idVysledku
RIV/49777513:23520/10:00504550
n3:jazykVysledku
n10:eng
n3:klicovaSlova
sign language; image processing; correlation analysis
n3:klicoveSlovo
n7:image%20processing n7:correlation%20analysis n7:sign%20language
n3:kontrolniKodProRIV
[C5AC9ACF737A]
n3:mistoKonaniAkce
Beijing
n3:mistoVydani
Beijing
n3:nazevZdroje
2010 IEEE 10th International Conference on Signal Processing Proceedings
n3:obor
n21:JD
n3:pocetDomacichTvurcuVysledku
3
n3:pocetTvurcuVysledku
3
n3:projekt
n18:GP102%2F09%2FP609 n18:ME08106
n3:rokUplatneniVysledku
n4:2010
n3:tvurceVysledku
Hrúz, Marek Campr, Pavel Krňoul, Zdeněk
n3:typAkce
n15:WRD
n3:zahajeniAkce
2010-01-01+01:00
s:numberOfPages
4
n8:hasPublisher
Institute of Electrical and Electronics Engineers, Inc.
n11:isbn
978-1-4244-5898-1
n19:organizacniJednotka
23520